scholarly article | Q13442814 |
P6179 | Dimensions Publication ID | 1042502685 |
P356 | DOI | 10.1038/NM0102-68 |
P8608 | Fatcat ID | release_7aer4mld6zbgxiyftry4xzob7m |
P3181 | OpenCitations bibliographic resource ID | 789511 |
P698 | PubMed publication ID | 11786909 |
P5875 | ResearchGate publication ID | 11571355 |
P50 | author | Eric Lander | Q970550 |
Todd Golub | Q7812388 | ||
Jill P. Mesirov | Q19664665 | ||
Michelle Gaasenbeek | Q28914670 | ||
Pablo Tamayo | Q59551108 | ||
Margaret A Shipp | Q89030667 | ||
Geraldine Pinkus | Q110078288 | ||
P2093 | author name string | Jeffery L Kutok | |
Jon C Aster | |||
Donna S Neuberg | |||
T Andrew Lister | |||
Ricardo C T Aguiar | |||
Andrew Norton | |||
Michael Reich | |||
Andrew P Weng | |||
Michael Angelo | |||
Ken N Ross | |||
Kim W Last | |||
Margaret A Koval | |||
Tane S Ray | |||
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P433 | issue | 1 | |
P407 | language of work or name | English | Q1860 |
P921 | main subject | machine learning | Q2539 |
diffuse large B-cell lymphoma | Q2626074 | ||
B-cell lymphoma | Q4833719 | ||
P304 | page(s) | 68-74 | |
P577 | publication date | 2002-01-01 | |
P1433 | published in | Nature Medicine | Q1633234 |
P1476 | title | Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning | |
P478 | volume | 8 |
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Q44249820 | Essential role of caveolae in interleukin-6- and insulin-like growth factor I-triggered Akt-1-mediated survival of multiple myeloma cells |
Q30978092 | Evaluating methods for classifying expression data |
Q53388123 | Evolving-Pattern Analysis of Transient and Long-Term Biomarkers for Cancers: Hepatocellular Carcinoma as a Case. |
Q53615601 | Evolving-pattern analysis of transient and long-term biomarkers for cancers: Hepatocellular carcinoma as a case. |
Q51967988 | Experimental trial for diagnosis of pancreatic ductal carcinoma based on gene expression profiles of pancreatic ductal cells. |
Q73314540 | Exploring Primary Cutaneous B-Cell Lymphoma by Microarray Technology |
Q33859180 | Exploring the within- and between-class correlation distributions for tumor classification |
Q52565931 | Expression and prognostic implications of cell cycle regulatory molecules, p16, p21, p27, p14 and p53 in germinal centre and non-germinal centre B-like diffuse large B-cell lymphomas. |
Q33209668 | Expression genomics and cancer biology |
Q54644145 | Expression of C-IAP1, C-IAP2 and SURVIVIN discriminates different types of lymphoid malignancies. |
Q36865089 | Expression of DBC1 and Androgen Receptor Predict Poor Prognosis in Diffuse Large B Cell Lymphoma |
Q80670802 | Expression of HGAL in primary cutaneous large B-cell lymphomas: evidence for germinal center derivation of primary cutaneous follicular lymphoma |
Q63633924 | Expression of PD-1 (CD279) and FoxP3 in diffuse large B-cell lymphoma |
Q81791444 | Expression of PKC-beta or cyclin D2 predicts for inferior survival in diffuse large B-cell lymphoma |
Q46724259 | Expression of TNF-receptor associated factor 2 correlates with poor progression-free survival time in ABC-like primary nodal diffuse large B-cell lymphomas |
Q54602143 | Expression of ice, bcl-2, c-myc and p53 in different bone marrow cell populations from patients with diffuse large B-cell lymphoma. |
Q25256909 | Expression of minichromosome maintenance protein 2 as a marker for proliferation and prognosis in diffuse large B-cell lymphoma: a tissue microarray and clinico-pathological analysis. |
Q44655400 | Expression of nm23‐H1 is associated with poor prognosis in peripheral T‐cell lymphoma |
Q46955817 | Expression of the bcl-6 and MUM1/IRF4 proteins correlate with overall and disease-specific survival in patients with primary cutaneous large B-cell lymphoma: a tissue microarray study |
Q42538635 | Expression of the human germinal center-associated lymphoma (HGAL) protein, a new marker of germinal center B-cell derivation |
Q35770767 | Expression of the polycomb-group gene BMI1 is related to an unfavourable prognosis in primary nodal DLBCL. |
Q57636725 | Expression profile of translation initiation factor eIF2B5 in diffuse large B-cell lymphoma and its correlation to clinical outcome |
Q40631853 | Expression profiling targeting chromosomes for tumor classification and prediction of clinical behavior. |
Q33378247 | Expression-based Pathway Signature Analysis (EPSA): mining publicly available microarray data for insight into human disease |
Q30824314 | Extending the utility of gene profiling data by bridging microarray platforms. |
Q36558024 | Extrinsic versus intrinsic apoptosis pathways in anticancer chemotherapy |
Q53515118 | FDG-PET after 1 cycle of therapy predicts outcome in diffuse large cell lymphoma and classic Hodgkin disease. |
Q36871999 | FOXP1: a potential therapeutic target in cancer. |
Q47606657 | Factors predicting long-term survival in low-risk diffuse large B-cell lymphoma |
Q46957617 | Fas and Fas ligand expression on germinal center type-diffuse large B-cell lymphoma is associated with the clinical outcome |
Q36005212 | Feature Selection and Cancer Classification via Sparse Logistic Regression with the Hybrid L1/2 +2 Regularization |
Q35756955 | Feature selection and molecular classification of cancer using genetic programming |
Q58101114 | Feature selection of gene expression data for Cancer classification using double RBF-kernels |
Q30478162 | Feature selection using Haar wavelet power spectrum |
Q33526505 | FiGS: a filter-based gene selection workbench for microarray data |
Q39328378 | Finding a helix in a haystack: nucleic acid cytometry with droplet microfluidics |
Q34351520 | Finding minimum gene subsets with heuristic breadth-first search algorithm for robust tumor classification |
Q35240801 | Finding top-k covering irreducible contrast sequence rules for disease diagnosis. |
Q35008948 | Focus on lymphomas |
Q41887389 | Fold change rank ordering statistics: a new method for detecting differentially expressed genes. |
Q35073307 | From microarrays to new therapeutic approaches in bladder cancer. |
Q30749843 | From patterns to pathways: gene expression data analysis comes of age. |
Q37136999 | Front-line therapy for nonlocalized diffuse large B-cell lymphoma: what has been demonstrated and what is yet to be established. |
Q36192439 | Frontline rituximab, cyclophosphamide, doxorubicin, and prednisone with bortezomib (VR-CAP) or vincristine (R-CHOP) for non-GCB DLBCL. |
Q36150368 | Functional genomic analysis of cancer metastasis: biologic insights and clinical implications |
Q39420364 | Functional networks inference from rule-based machine learning models. |
Q42637800 | Functional signatures identified in B-cell non-Hodgkin lymphoma profiles. |
Q52027273 | Fuzzy neural network applied to gene expression profiling for predicting the prognosis of diffuse large B-cell lymphoma. |
Q53508384 | Ga-67 SPECT: ave atque vale! Or have we bid a premature farewell to a trusted friend? |
Q38354055 | Gain-of-function mutations and copy number increases of Notch2 in diffuse large B-cell lymphoma |
Q36440083 | Galectin-3 binds to CD45 on diffuse large B-cell lymphoma cells to regulate susceptibility to cell death |
Q33561477 | Gene Feature Extraction Based on Nonnegative Dual Graph Regularized Latent Low-Rank Representation |
Q37738446 | Gene arrays in lymphoma: Where will they fit in? |
Q26825706 | Gene expression analysis in RA: towards personalized medicine |
Q36673583 | Gene expression array profile of human osteosarcoma |
Q33381434 | Gene expression data classification using consensus independent component analysis |
Q30724775 | Gene expression in cancer: the application of microarrays |
Q46042728 | Gene expression patterns in AIDS versus non-AIDS-related diffuse large B-cell lymphoma |
Q38354504 | Gene expression phenotypic models that predict the activity of oncogenic pathways |
Q42432005 | Gene expression predicts overall survival in paraffin-embedded tissues of diffuse large B-cell lymphoma treated with R-CHOP. |
Q35661018 | Gene expression profiling and its application in studies of haematological malignancy. |
Q38519535 | Gene expression profiling identifies molecular subgroups among nodal peripheral T-cell lymphomas. |
Q37074127 | Gene expression profiling in autoimmune noninfectious uveitis disease |
Q36799850 | Gene expression profiling in diffuse large B-cell lymphoma |
Q38513479 | Gene expression profiling of diffuse large B-cell lymphoma supervised by CD21 expression |
Q36613726 | Gene expression profiling of primary cultures of ovarian epithelial cells identifies novel molecular classifiers of ovarian cancer. |
Q77856791 | Gene expression profiling to predict lymphoma outcome |
Q36050530 | Gene expression profiling using RNA extracted from whole blood: technologies and clinical applications |
Q104795172 | Gene expression profiling-based risk prediction and profiles of immune infiltration in diffuse large B-cell lymphoma |
Q35758712 | Gene expression profiling: from microarrays to medicine. |
Q35573313 | Gene expression profiling: will it complement or replace immunophenotyping? |
Q36568849 | Gene expression signatures and outcome prediction in mature B-cell malignancies |
Q44828229 | Gene expression signatures in lymphoid tumours |
Q36678558 | Gene expression-based screening for inhibitors of PDGFR signaling |
Q30584472 | Gene selection and cancer type classification of diffuse large-B-cell lymphoma using a bivariate mixture model for two-species data |
Q34173671 | Gene selection and classification for cancer microarray data based on machine learning and similarity measures |
Q36100658 | Gene selection for cancer classification with the help of bees |
Q31132175 | Gene selection for classification of microarray data based on the Bayes error |
Q35208950 | Gene selection for multiclass prediction by weighted Fisher criterion |
Q30807880 | Gene selection in microarray data: the elephant, the blind men and our algorithms |
Q36295294 | Gene set enrichment analysis unveils the mechanism for the phosphodiesterase 4B control of glucocorticoid response in B-cell lymphoma |
Q35146553 | Gene-expression profiling in human cutaneous melanoma |
Q36690245 | Gene-expression signatures in oncology diagnostics |
Q28276837 | Genes associated with the tumour microenvironment are differentially expressed in cured versus primary chemotherapy-refractory diffuse large B-cell lymphoma |
Q24798750 | Genetic alteration and gene expression modulation during cancer progression |
Q35985492 | Genomic and proteomic approaches for studying human cancer: prospects for true patient-tailored therapy |
Q37363928 | Genomic and proteomic biomarkers for cancer: a multitude of opportunities. |
Q37406963 | Genomic approaches to small molecule discovery |
Q38042513 | Genomic profiling using array comparative genomic hybridization define distinct subtypes of diffuse large B-cell lymphoma: a review of the literature |
Q36303896 | Genomics in breast cancer-therapeutic implications |
Q40949651 | Genotyping on a thermal gradient DNA chip |
Q43137033 | Germinal center B cell-like (GCB) and activated B cell-like (ABC) type of diffuse large B cell lymphoma (DLBCL): analysis of molecular predictors, signatures, cell cycle state and patient survival. |
Q35121615 | Global Gene Expression Profiling in the Study of Multiple Myeloma |
Q80265745 | Global gene expression profiling of formalin-fixed paraffin-embedded tumor samples: a comparison to snap-frozen material using oligonucleotide microarrays |
Q34276961 | Google goes cancer: improving outcome prediction for cancer patients by network-based ranking of marker genes |
Q93012478 | Guidelines for using sigQC for systematic evaluation of gene signatures |
Q35206356 | HLA class II antibodies in the treatment of hematologic malignancies |
Q91949197 | Hellinger distance-based stable sparse feature selection for high-dimensional class-imbalanced data |
Q38433314 | Heterogeneity of protein kinase C beta(2) expression in lymphoid malignancies |
Q53662425 | High Ki-67 expression in involved bone marrow predicts worse clinical outcome in diffuse large B cell lymphoma patients treated with R-CHOP therapy. |
Q28206624 | High level of cannabinoid receptor 1, absence of regulator of G protein signalling 13 and differential expression of Cyclin D1 in mantle cell lymphoma |
Q37335051 | High resolution array comparative genomic hybridization identifies copy number alterations in diffuse large B-cell lymphoma that predict response to immuno-chemotherapy |
Q83820573 | High throughput tissue microarray analysis of FHIT expression in diffuse large cell B-cell lymphoma from Saudi Arabia |
Q28740452 | High-dimensional pharmacogenetic prediction of a continuous trait using machine learning techniques with application to warfarin dose prediction in African Americans |
Q58908211 | High-dose chemotherapy with autologous stem cell support for first-line treatment of aggressive non-Hodgkin lymphoma: a systematic review and meta-analysis based on individual patient data |
Q50485002 | High-resolution loss of heterozygosity screening implicates PTPRJ as a potential tumor suppressor gene that affects susceptibility to Non-Hodgkin's lymphoma. |
Q45899999 | Higher response to lenalidomide in relapsed/refractory diffuse large B-cell lymphoma in nongerminal center B-cell-like than in germinal center B-cell-like phenotype. |
Q53437646 | History of haematopoietic stem-cell transplantation. |
Q43011229 | How do we define Hodgkin's disease? The authors' reply |
Q64121066 | I-Boost: an integrative boosting approach for predicting survival time with multiple genomics platforms |
Q40614440 | INCORPORATING BIOLOGICAL INFORMATION INTO LINEAR MODELS: A BAYESIAN APPROACH TO THE SELECTION OF PATHWAYS AND GENES. |
Q78427251 | Identification and validation of seven genes, as potential markers, for the differential diagnosis of small B cell lymphomas (small lymphocytic lymphoma, marginal zone B cell lymphoma and mantle cell lymphoma) by cDNA macroarrays analysis |
Q92628694 | Identification of CD4+ T cell biomarkers for predicting the response of patients with relapsing‑remitting multiple sclerosis to natalizumab treatment |
Q37661495 | Identification of Marker Genes for Cancer Based on Microarrays Using a Computational Biology Approach. |
Q31109027 | Identification of a robust gene signature that predicts breast cancer outcome in independent data sets |
Q35018604 | Identification of candidate B-lymphoma genes by cross-species gene expression profiling |
Q43766905 | Identification of differentially expressed proteins in chemotherapy-sensitive and chemotherapy-resistant diffuse large B cell lymphoma by proteomic methods |
Q24791397 | Identification of expressed genes linked to malignancy of human colorectal carcinoma by parametric clustering of quantitative expression data |
Q76312993 | Identification of genes whose expression patterns differ in benign lymphoid tissue and follicular, mantle cell, and small lymphocytic lymphoma |
Q41365240 | Identification of key lncRNAs in colorectal cancer progression based on associated protein-protein interaction analysis |
Q36047432 | Identification of metastasis-suppressive microRNAs in primary melanoma |
Q48332534 | Identification of molecular subtypes of glioblastoma by gene expression profiling |
Q93079390 | Identifying Methylation Pattern and Genes Associated with Breast Cancer Subtypes |
Q52111529 | Identifying distinct classes of bladder carcinoma using microarrays. |
Q89811270 | Identifying transcriptional profiles and evaluating prognostic biomarkers of HIV-associated diffuse large B-cell lymphoma from Malawi |
Q28536423 | Immune response to combination therapy for non-Hodgkin lymphomas |
Q33700531 | Immunohistochemical and molecular characteristics with prognostic significance in diffuse large B-cell lymphoma |
Q51514379 | Immunohistochemical detection of MYC protein correlates with MYC gene status in aggressive B cell lymphomas. |
Q80270939 | Immunohistochemical detection of protein kinase C-beta (PKC-beta) in tumour specimens of patients with non-small cell lung cancer |
Q45372503 | Immunohistochemical expression profile and prognosis in patients with diffuse large B-cell lymphoma with or without human immunodeficiency virus infection |
Q44813152 | Immunohistochemical profile and prognostic significance in primary central nervous system lymphoma: Analysis of 89 cases |
Q33561185 | Immunophenotypic analysis of AIDS-related diffuse large B-cell lymphoma and clinical implications in patients from AIDS Malignancies Consortium clinical trials 010 and 034 |
Q60548642 | Impact of ecological redundancy on the performance of machine learning classifiers in vegetation mapping |
Q37831960 | Impact of gene expression profiling in lymphoma diagnosis and prognosis. |
Q35806762 | Impact of microarray technology in clinical oncology |
Q53112598 | Impact of occult bone marrow involvement on the outcome of rituximab plus cyclophosphamide, doxorubicin, vincristine and prednisone therapy for diffuse large B-cell lymphoma. |
Q57174076 | Implications of STAT3 and STAT5 signaling on gene regulation and chromatin remodeling in hematopoietic cancer |
Q31105470 | Importance of data structure in comparing two dimension reduction methods for classification of microarray gene expression data |
Q34475554 | Improving accuracy for cancer classification with a new algorithm for genes selection |
Q33784190 | Improving cancer classification accuracy using gene pairs |
Q39841564 | In Vivo Measurements of Tumor Metabolism and Growth after Administration of Enzastaurin Using Small Animal FDG Positron Emission Tomography |
Q33701036 | In silico analyses reveal common cellular pathways affected by loss of heterozygosity (LOH) events in the lymphomagenesis of Non-Hodgkin's lymphoma (NHL). |
Q81413385 | Incidence of diffuse large B-cell lymphoma of germinal center B-cell origin in whole diffuse large B-cell lymphoma: tissue fluorescence in situ hybridization using t(14;18) compared with immunohistochemistry |
Q104795127 | Incidence of relapsed/refractory diffuse large B-cell lymphoma (DLBCL) including CNS relapse in a population-based cohort of 4243 patients in Sweden |
Q33800442 | Increased MYC gene copy number correlates with increased mRNA levels in diffuse large B-cell lymphoma |
Q31041309 | Independent component analysis-based penalized discriminant method for tumor classification using gene expression data |
Q36318541 | Individualised cancer therapeutics: dream or reality? |
Q44898962 | Infused CD34 cell dose, but not tumour cell content of peripheral blood progenitor cell grafts, predicts clinical outcome in patients with diffuse large B-cell lymphoma and follicular lymphoma grade 3 treated with high-dose therapy |
Q44349388 | Inhibition of FLT3 in MLL. Validation of a therapeutic target identified by gene expression based classification |
Q34860750 | Inhibition of bromodomain proteins for the treatment of human diffuse large B-cell lymphoma. |
Q35670308 | Inhibition of β-catenin signaling by nongenomic action of orphan nuclear receptor Nur77 |
Q35811338 | Injury research in the genomic era. |
Q24645231 | Insig2 is associated with colon tumorigenesis and inhibits Bax-mediated apoptosis |
Q35818443 | Insights into the Molecular Pathogenesis of Activated B-Cell-like Diffuse Large B-Cell Lymphoma and Its Therapeutic Implications |
Q34375924 | Integrated modeling of clinical and gene expression information for personalized prediction of disease outcomes |
Q51490388 | Integrated profiling of diffuse large B-cell lymphoma with 7q gain. |
Q35416193 | Integrating biological knowledge with gene expression profiles for survival prediction of cancer |
Q78512453 | Integrating cytogenetics and gene expression profiling in the molecular analysis of multiple myeloma |
Q30854282 | Integrative clustering methods for high-dimensional molecular data |
Q35170930 | Interpreting the molecular biology and clinical behavior of multiple myeloma in the context of global gene expression profiling |
Q36925740 | Investigating the efficacy of nonlinear dimensionality reduction schemes in classifying gene and protein expression studies |
Q35096214 | Issues and progress with protein kinase inhibitors for cancer treatment |
Q33412905 | Iterative Bayesian Model Averaging: a method for the application of survival analysis to high-dimensional microarray data |
Q35832755 | Joint use of over- and under-sampling techniques and cross-validation for the development and assessment of prediction models |
Q31044239 | Kernel-based distance metric learning for microarray data classification |
Q60502894 | Knowledge-based neural networks for gene expression data analysis, modelling and profile discovery |
Q24814110 | L2L: a simple tool for discovering the hidden significance in microarray expression data |
Q33648588 | LMP1+SLAMF1high cells are associated with drug resistance in Epstein-Barr virus-positive Farage cells |
Q44125775 | Lack of prognostic significance of the germinal-center phenotype in diffuse large B-cell lymphoma patients treated with CHOP-like chemotherapy with and without rituximab |
Q64916006 | Large-Scale Automatic Feature Selection for Biomarker Discovery in High-Dimensional OMICs Data. |
Q29615223 | Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression |
Q92236955 | Learning misclassification costs for imbalanced classification on gene expression data |
Q36059635 | Lesional gene expression profiling in cutaneous T-cell lymphoma reveals natural clusters associated with disease outcome |
Q33633714 | Local-learning-based feature selection for high-dimensional data analysis |
Q35634835 | Looking beyond morphology: cancer gene expression profiling using DNA microarrays |
Q37406798 | Loss of HLA-DR expression and immunoblastic morphology predict adverse outcome in diffuse large B-cell lymphoma - analyses of cases from two prospective randomized clinical trials |
Q41092345 | Loss of HLA-DR expression is related to tumor microenvironment and predicts adverse outcome in diffuse large B-cell lymphoma |
Q35978570 | Loss of IRF8 Inhibits the Growth of Diffuse Large B-cell Lymphoma |
Q38329996 | Loss of expression of the adipocyte-type fatty acid-binding protein (A-FABP) is associated with progression of human urothelial carcinomas |
Q35850018 | Loss of major histocompatibility class II expression in non-immune-privileged site diffuse large B-cell lymphoma is highly coordinated and not due to chromosomal deletions. |
Q37453629 | Low GILT Expression is Associated with Poor Patient Survival in Diffuse Large B-Cell Lymphoma |
Q34162187 | Lymphoid malignancies: the dark side of B-cell differentiation |
Q36959865 | Lymphoma microenvironment: culprit or innocent? |
Q28589356 | M17, a gene specific for germinal center (GC) B cells and a prognostic marker for GC B-cell lymphomas, is dispensable for the GC reaction in mice |
Q44544162 | MAGE-A3 expression is an adverse prognostic factor in diffuse large B-cell lymphoma |
Q63409870 | MALT1 directs B cell receptor–induced canonical nuclear factor-κB signaling selectively to the c-Rel subunit |
Q37470505 | MET/PKCbeta expression correlate with metastasis and inhibition is synergistic in lung cancer |
Q38233772 | MYC-associated and double-hit lymphomas: a review of pathobiology, prognosis, and therapeutic approaches |
Q63881018 | Machine Learning Methods as a Tool for Predicting Risk of Illness Applying Next‐Generation Sequencing Data |
Q98164806 | Machine learning in oncology: a review |
Q57175155 | Maintenance Therapy in Diffuse Large B Cell Lymphoma and Mantle Cell Lymphoma |
Q78581893 | Mature T cell leukemias which cannot be adequately classified under the new WHO classification of lymphoid neoplasms |
Q37743310 | Maxdenominator Reweighted Sparse Representation for Tumor Classification |
Q35967033 | McTwo: a two-step feature selection algorithm based on maximal information coefficient |
Q33928495 | Mechanism-derived gene expression signatures and predictive biomarkers in clinical oncology |
Q35010175 | Medical applications of microarray technologies: a regulatory science perspective |
Q31110581 | Meta-analysis of gene expression data: a predictor-based approach |
Q97525205 | Metabolic Adaptations in Cancer Stem Cells |
Q34008985 | Metastasis of tumor cells is enhanced by downregulation of Bit1. |
Q39218802 | MicroRNA-21 regulates the sensitivity of diffuse large B-cell lymphoma cells to the CHOP chemotherapy regimen |
Q24528253 | Microarray analysis identifies a death-from-cancer signature predicting therapy failure in patients with multiple types of cancer |
Q36982175 | Microarray analysis of gene expression of cancer to guide the use of chemotherapeutics |
Q33320174 | Microarray based diagnosis profits from better documentation of gene expression signatures |
Q34044075 | Microarray-based cancer prediction using single genes |
Q37313817 | Microarray-based cancer prediction using soft computing approach |
Q38326709 | Microarray-based classification of diffuse large B-cell lymphoma |
Q24791738 | Microarrays and molecular markers for tumor classification |
Q34836984 | Microarrays in pharmacogenomics--advances and future promise |
Q36177378 | Microarrays in veterinary diagnostics |
Q36680069 | Microarrays to identify new therapeutic strategies for cancer |
Q38465717 | Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles |
Q64085609 | Microbiome Learning Repo (ML Repo): A public repository of microbiome regression and classification tasks |
Q35691640 | Microvessel density and expression of vascular endothelial growth factor and its receptors in diffuse large B-cell lymphoma subtypes |
Q36868498 | Mining gene expression profiles: expression signatures as cancer phenotypes |
Q36558011 | Mitochondria in hematopoiesis and hematological diseases. |
Q37061820 | Mitogenic Effect of Orphan Receptor TR3 and Its Regulation by MEKK1 in Lung Cancer Cells |
Q36344970 | Mobile Genome Express (MGE): A comprehensive automatic genetic analyses pipeline with a mobile device |
Q31112220 | Model order selection for bio-molecular data clustering |
Q51220498 | Modified signal-to-noise: a new simple and practical gene filtering approach based on the concept of projective adaptive resonance theory (PART) filtering method. |
Q37185837 | Modulation of orphan nuclear receptor Nur77-mediated apoptotic pathway by acetylshikonin and analogues |
Q34741163 | Molecular cancer classification using a meta-sample-based regularized robust coding method |
Q35102952 | Molecular classification of parathyroid neoplasia by gene expression profiling |
Q35670986 | Molecular heterogeneity of diffuse large B-cell lymphoma: implications for disease management and prognosis |
Q51075776 | Molecular impact of selective NFKB1 and NFKB2 signaling on DLBCL phenotype. |
Q35917589 | Molecular medicine: a clinician's primer on microarrays. |
Q84767205 | Molecular pathogenesis of diffuse large B-cell lymphoma |
Q38065892 | Molecular pathology of lymphoma |
Q35010198 | Molecular portraits and the family tree of cancer |
Q36381346 | Molecular profiling reveals prognostically significant subtypes of canine lymphoma |
Q36168697 | Molecular prognostic factors in diffuse large B-cell lymphoma |
Q79934103 | Molecular signatures in biopsy specimens of lung cancer |
Q36007355 | Molecular signatures of lymphoma |
Q36239669 | Monoclonal antibody therapy of leukaemias and lymphomas |
Q38179500 | Moving beyond rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone for diffuse large B-cell lymphoma |
Q99607473 | Multi-scale supervised clustering-based feature selection for tumor classification and identification of biomarkers and targets on genomic data |
Q30763386 | Multi-task feature selection in microarray data by binary integer programming |
Q24793866 | Multiclass classification of microarray data with repeated measurements: application to cancer |
Q35747661 | Multicolor-FICTION: expanding the possibilities of combined morphologic, immunophenotypic, and genetic single cell analyses |
Q35755485 | Multiparameter analysis of homogeneously R-CHOP-treated diffuse large B cell lymphomas identifies CD5 and FOXP1 as relevant prognostic biomarkers: report of the prospective SAKK 38/07 study. |
Q47445559 | Multiple fuzzy neural network system for outcome prediction and classification of 220 lymphoma patients on the basis of molecular profiling |
Q39753010 | Multiplex polymerase chain reaction-based prognostic models in diffuse large B-cell lymphoma patients treated with R-CHOP. |
Q40438326 | Multiplex reverse transcription-polymerase chain reaction combined with on-chip electrophoresis as a rapid screening tool for candidate gene sets |
Q36447932 | Mutations in the DNA-binding codons of TP53, which are associated with decreased expression of TRAILreceptor-2, predict for poor survival in diffuse large B-cell lymphoma |
Q37638021 | NEK2 induces drug resistance mainly through activation of efflux drug pumps and is associated with poor prognosis in myeloma and other cancers |
Q35586784 | Neoadjuvant comparisons of aromatase inhibitors and tamoxifen: pretreatment determinants of response and on-treatment effect |
Q89926626 | Network modeling of patients' biomolecular profiles for clinical phenotype/outcome prediction |
Q34427904 | Network-based Prediction of Cancer under Genetic Storm |
Q24796756 | Neural network analysis of lymphoma microarray data: prognosis and diagnosis near-perfect |
Q31122605 | New insights into ADPKD molecular pathways using combination of SAGE and microarray technologies |
Q91276848 | New machine-learning technologies for computer-aided diagnosis |
Q35063883 | New molecular methods for classification, diagnosis and therapy prediction of hematological malignancies |
Q37918027 | New strategies in diffuse large B-cell lymphoma: translating findings from gene expression analyses into clinical practice |
Q26796428 | Next-generation prognostic assessment for diffuse large B-cell lymphoma |
Q37457207 | Nodal diffuse large B-cell lymphomas in children and adolescents: immunohistochemical expression patterns and c-MYC translocation in relation to clinical outcome |
Q44228664 | Non-Hodgkin's lymphoma in the microarray era. |
Q34328089 | Non-invasive mapping of the gastrointestinal microbiota identifies children with inflammatory bowel disease |
Q40863355 | Non-negative matrix factorization by maximizing correntropy for cancer clustering |
Q37858532 | Novel agents for diffuse large B-cell lymphoma |
Q36616528 | Novel approaches for the management of patients with Ewing sarcoma |
Q37775632 | Novel disease targets and management approaches for diffuse large B-cell lymphoma |
Q31028064 | Novel prognostic genes of diffuse large B-cell lymphoma revealed by survival analysis of gene expression data |
Q36871990 | Novel therapeutic targets in mantle cell lymphoma |
Q35111768 | Novel therapeutics for aggressive non-Hodgkin's lymphoma |
Q36429727 | Novel treatment strategies for aggressive non-Hodgkin's lymphoma |
Q59117821 | On Feature Selection and Rule Extraction for High Dimensional Data: A Case of Diffuse Large B-Cell Lymphomas Microarrays Classification |
Q24645617 | Onco-miR-155 targets SHIP1 to promote TNFalpha-dependent growth of B cell lymphomas |
Q37295261 | Oncologist's/haematologist's view on the roles of pathologists for molecular targeted cancer therapy |
Q54364450 | Open-label, single-arm, phase II study of enzastaurin in patients with follicular lymphoma. |
Q35008943 | Optimal gene expression analysis by microarrays |
Q33822080 | Optimization based tumor classification from microarray gene expression data. |
Q44394901 | Optimization of quantitative real-time RT-PCR parameters for the study of lymphoid malignancies |
Q30749830 | Options available--from start to finish--for obtaining data from DNA microarrays II. |
Q33551720 | Overexpression of an activated REL mutant enhances the transformed state of the human B-lymphoma BJAB cell line and alters its gene expression profile |
Q37940364 | Overview of microarrays in drug discovery and development |
Q37644833 | PATZ1 expression correlates positively with BAX and negatively with BCL6 and survival in human diffuse large B cell lymphomas |
Q38996724 | PD-1-PD-L1 immune-checkpoint blockade in B-cell lymphomas |
Q43462759 | PKC-beta II expression has prognostic impact in nodal diffuse large B-cell lymphoma |
Q28509628 | PKC-beta controls I kappa B kinase lipid raft recruitment and activation in response to BCR signaling |
Q38323206 | PROX1 overexpression inhibits protein kinase C beta II transcription through promoter DNA methylation |
Q36713498 | Paraffin-based 6-gene model predicts outcome in diffuse large B-cell lymphoma patients treated with R-CHOP. |
Q37403682 | Pathophysiology of retinal lymphoma |
Q34721895 | Pathway activity inference for multiclass disease classification through a mathematical programming optimisation framework |
Q44564603 | Patients with high-risk aggressive lymphoma treated with frontline intensive chemotherapy and autografting: evidence of marked differences in outcome between patients with age-adjusted International Prognostic Index scores 2 and 3. |
Q38127385 | Pediatric lymphoma diagnosis: role of FNAC, biopsy, immunohistochemistry and molecular diagnostics |
Q34695697 | Pharmacogenomic strategies provide a rational approach to the treatment of cisplatin-resistant patients with advanced cancer |
Q42115619 | Pharmacological manipulation of Bcl-2 family members to control cell death |
Q37554503 | Phospho-p70S6K and cdc2/cdk1 as therapeutic targets for diffuse large B-cell lymphoma |
Q38984735 | Phosphodiesterase 4 inhibitors have wide-ranging activity in B-cell malignancies |
Q30759423 | Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification |
Q85804046 | Precision treatment of distinct molecular subtypes of diffuse large B-cell lymphoma: ascribing treatment based on the molecular phenotype |
Q64085970 | Predicting Complete Remission of Acute Myeloid Leukemia: Machine Learning Applied to Gene Expression |
Q45728735 | Predicting hepatitis B virus-positive metastatic hepatocellular carcinomas using gene expression profiling and supervised machine learning |
Q36780164 | Predicting the outcome in non-Hodgkin lymphoma with molecular markers |
Q30578215 | Predicting the survival time for diffuse large B-cell lymphoma using microarray data |
Q35153794 | Prediction of survival in diffuse large B-cell lymphoma based on the expression of 2 genes reflecting tumor and microenvironment |
Q31134364 | Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets. |
Q40109282 | Predictive tests for individualization of pharmacological cancer treatment |
Q38872027 | Presence of simian virus 40 in diffuse large B-cell lymphomas in Tunisia correlates with germinal center B-cell immunophenotype, t(14;18) translocation, and P53 accumulation |
Q33598987 | Primary diffuse large B-cell lymphoma of the oral cavity: germinal center classification |
Q35089389 | Profiling cancer |
Q47738329 | Prognosis of localized diffuse large B-cell lymphoma in younger patients |
Q92885779 | Prognostic Nomogram for Overall Survival in Patients with Diffuse Large B-Cell Lymphoma |
Q36244809 | Prognostic efficacy of the human B-cell lymphoma prognostic genes in predicting disease-free survival (DFS) in the canine counterpart |
Q35548353 | Prognostic factors and risk-based therapy in pediatric acute myeloid leukemia |
Q34882773 | Prognostic factors for diffuse large B-cell lymphoma in the R(X)CHOP era. |
Q37635115 | Prognostic immunophenotypic biomarker studies in diffuse large B cell lymphoma with special emphasis on rational determination of cut-off scores. |
Q43146817 | Prognostic impact of protein kinase C beta II expression in R-CHOP-treated diffuse large B-cell lymphoma patients |
Q35587065 | Prognostic significance of CD44 expression in diffuse large B cell lymphoma of activated and germinal centre B cell-like types: a tissue microarray analysis of 90 cases |
Q43248488 | Prognostic significance of S-phase kinase-associated protein 2 and p27kip1 in patients with diffuse large B-cell lymphoma: effects of rituximab |
Q37706051 | Prognostic value of expression of nuclear factor kappa-B/p65 in non-GCB DLBCL patients. |
Q37833087 | Prognostication of diffuse large B-cell lymphoma in the rituximab era. |
Q35824980 | Progress in myeloma stem cells |
Q73401113 | Progressive disease following autologous transplantation in patients with chemosensitive relapsed or primary refractory Hodgkin's disease or aggressive non-Hodgkin's lymphoma |
Q79270324 | Promoter hypermethylation of the DNA-repair gene O6-methylguanine-DNA methyltransferase and p53 mutation in diffuse large B-cell lymphoma |
Q80413450 | Proof concept for clinical justification of network mapping for personalized cancer therapeutics |
Q35833866 | Pros and cons of microarray technology in allergy research |
Q42807725 | Protein expression and cellular localization in two prognostic subgroups of diffuse large B-cell lymphoma: higher expression of ZAP70 and PKC-beta II in the non-germinal center group and poor survival in patients deficient in nuclear PTEN. |
Q37020881 | Protein kinase C beta in malignant pleural mesothelioma |
Q43275999 | Protein kinase C-beta II expression in diffuse large B-cell lymphoma predicts for inferior outcome of anthracycline-based chemotherapy with and without rituximab |
Q35634280 | Protein kinase C-beta inhibition induces apoptosis and inhibits cell cycle progression in acquired immunodeficiency syndrome-related non-hodgkin lymphoma cells |
Q41971372 | Protein kinase C: an attractive target for cancer therapy. |
Q33569854 | Protein kinase Cbeta modulates ligand-induced cell surface death receptor accumulation: a mechanistic basis for enzastaurin-death ligand synergy. |
Q33197095 | Proteomic analysis of pulmonary edema fluid and plasma in patients with acute lung injury. |
Q35725628 | Proteomics and the haematologist. |
Q37696313 | Protocol for qRT-PCR analysis from formalin fixed paraffin embedded tissue sections from diffuse large b-cell lymphoma: Validation of the six-gene predictor score. |
Q36757502 | Quantitative image analysis in the assessment of diffuse large B-cell lymphoma |
Q38430790 | Quantitative nuclease protection assay in paraffin-embedded tissue replicates prognostic microarray gene expression in diffuse large-B-cell lymphoma |
Q38699741 | RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers |
Q42376068 | RIFS: a randomly restarted incremental feature selection algorithm. |
Q33357619 | RNA expression analysis from formalin fixed paraffin embedded tissues |
Q57277018 | RNA expression analysis of formalin-fixed paraffin-embedded tumors |
Q33941314 | RNA: state memory and mediator of cellular phenotype |
Q28397762 | Random generalized linear model: a highly accurate and interpretable ensemble predictor |
Q28834535 | Rapid Prediction of Bacterial Heterotrophic Fluxomics Using Machine Learning and Constraint Programming |
Q39982575 | Ratio adjustment and calibration scheme for gene-wise normalization to enhance microarray inter-study prediction |
Q37234623 | Rational combined targeting of phosphodiesterase 4B and SYK in DLBCL |
Q36150374 | Recent advances in the molecular diagnosis of diffuse large B-cell lymphoma |
Q34487811 | Regulation of Nur77 nuclear export by c-Jun N-terminal kinase and Akt. |
Q38210641 | Relapsed/refractory diffuse large B-cell lymphoma: review of the management of transplant-eligible patients |
Q24289394 | Reliability and reproducibility issues in DNA microarray measurements |
Q90077233 | Remaining challenges in predicting patient outcomes for diffuse large B-cell lymphoma |
Q28131820 | Repeated observation of breast tumor subtypes in independent gene expression data sets |
Q39938060 | Results of a multicentre UK-wide retrospective study evaluating the efficacy of pixantrone in relapsed, refractory diffuse large B cell lymphoma |
Q35750976 | Results of a randomized international study of high-risk central nervous system B non-Hodgkin lymphoma and B acute lymphoblastic leukemia in children and adolescents |
Q37598771 | Retinoid X receptor regulates Nur77/TR3-dependent apoptosis [corrected] by modulating its nuclear export and mitochondrial targeting |
Q35652930 | Retrospective analysis of protein kinase C-beta (PKC-beta) expression in lymphoid malignancies and its association with survival in diffuse large B-cell lymphomas |
Q34308389 | Revisiting global gene expression analysis |
Q35499320 | Risk Factors of Non-Hodgkin Lymphoma |
Q33407974 | Robust methods for accurate diagnosis using pan-microbiological oligonucleotide microarrays |
Q35740262 | Robust two-gene classifiers for cancer prediction |
Q40496898 | Role of CD21 antigen in diffuse large B-cell lymphoma and its clinical significance |
Q33256872 | Role of ancillary techniques in diagnosing and subclassifying non-Hodgkin's lymphomas on fine needle aspiration cytology |
Q55717558 | Role of microarray in cancer diagnosis. |
Q30605582 | SMOTE for high-dimensional class-imbalanced data |
Q24295903 | STAT5 represses BCL6 expression by binding to a regulatory region frequently mutated in lymphomas |
Q39472422 | Safety and Pharmacodynamics of the PDE4 Inhibitor Roflumilast in Advanced B-cell Malignancies |
Q48458182 | Safety, tolerability, QTc evaluation, and pharmacokinetics of single and multiple doses of enzastaurin HCl (LY317615), a protein kinase C-beta inhibitor, in healthy subjects. |
Q51335591 | Selection of causal gene sets for lymphoma prognostication from expression profiling and construction of prognostic fuzzy neural network models. |
Q35098956 | Selective model averaging with bayesian rule learning for predictive biomedicine |
Q24804682 | Semi-supervised methods to predict patient survival from gene expression data |
Q36471600 | Semiautomated multiplexed quantum dot-based in situ hybridization and spectral deconvolution |
Q33312689 | Serum diagnosis of diffuse large B-cell lymphomas and further identification of response to therapy using SELDI-TOF-MS and tree analysis patterning |
Q86022539 | Serum profiling by mass spectrometry combined with bioinformatics for the biomarkers discovery in diffuse large B-cell lymphoma |
Q91579802 | ShinyLearner: A containerized benchmarking tool for machine-learning classification of tabular data |
Q37829224 | Signal transduction inhibitor therapy for lymphoma |
Q35666703 | Signaling in transitional type 2 B cells is critical for peripheral B-cell development |
Q38150876 | Signaling pathways in lymphoma: pathogenesis and therapeutic targets |
Q41735339 | Simple decision rules for classifying human cancers from gene expression profiles |
Q34777109 | Sparse logistic regression with a L1/2 penalty for gene selection in cancer classification |
Q33419874 | Sparse representation for classification of tumors using gene expression data |
Q37616792 | Sparse representation for tumor classification based on feature extraction using latent low-rank representation. |
Q51806652 | Spontaneous high-titered IgG antibody responses against BCL-2 in patients with aggressive lymphomas. |
Q35518656 | Sputnik: ad hoc distributed computation. |
Q89751386 | State-of-the-Art Machine Learning Techniques Aiming to Improve Patient Outcomes Pertaining to the Cardiovascular System |
Q24678378 | Statistical analysis of an RNA titration series evaluates microarray precision and sensitivity on a whole-array basis |
Q37284250 | Statistical challenges in preprocessing in microarray experiments in cancer |
Q35789866 | Statistical considerations for immunohistochemistry panel development after gene expression profiling of human cancers |
Q35984039 | Structured feature selection using coordinate descent optimization. |
Q44704125 | Studies of the potential utility of Ki67 as a predictive molecular marker of clinical response in primary breast cancer |
Q35080295 | Study of suboptimum treatment response: lessons from breast cancer |
Q31137364 | Subclass mapping: identifying common subtypes in independent disease data sets |
Q37179385 | Subgraph augmented non-negative tensor factorization (SANTF) for modeling clinical narrative text |
Q39375022 | Super-SILAC allows classification of diffuse large B-cell lymphoma subtypes by their protein expression profiles |
Q31043807 | Support vector machines for dyadic data |
Q33259095 | Suppression of Mcl-1 via RNA interference sensitizes human hepatocellular carcinoma cells towards apoptosis induction. |
Q42702972 | Surface-antigen expression profiling of B cell chronic lymphocytic leukemia: from the signature of specific disease subsets to the identification of markers with prognostic relevance |
Q58776059 | Survival associated alternative splicing events in diffuse large B-cell lymphoma |
Q44864120 | Survival prediction of diffuse large-B-cell lymphoma based on both clinical and gene expression information |
Q47300115 | Synergistic targeting of the regulatory and catalytic subunits of PI3Kδ in mature B cell malignancies |
Q24298072 | TLE1 is an anoikis regulator and is downregulated by Bit1 in breast cancer cells |
Q89867359 | TMEM30A loss-of-function mutations drive lymphomagenesis and confer therapeutically exploitable vulnerability in B-cell lymphoma |
Q41908005 | TSG: a new algorithm for binary and multi-class cancer classification and informative genes selection |
Q37766121 | Targeted treatment and new agents in diffuse large B cell lymphoma |
Q34588195 | Targeting Nur77 translocation |
Q35628888 | Targeting PKC in multiple myeloma: in vitro and in vivo effects of the novel, orally available small-molecule inhibitor enzastaurin (LY317615.HCl). |
Q38184819 | The 'omics' of adrenocortical tumours for personalized medicine. |
Q36812744 | The Influence of the Global Gene Expression Shift on Downstream Analyses |
Q41909242 | The Role of mTOR Inhibitors for the Treatment of B-Cell Lymphomas |
Q34622215 | The SUV and FLT PET: a tasty alphabet soup or a dog's breakfast? |
Q34956078 | The T-cell response in patients with cancer |
Q91658641 | The Unsolved Puzzle of c-Rel in B Cell Lymphoma |
Q53153100 | The absolute monocyte and lymphocyte prognostic score predicts survival and identifies high-risk patients in diffuse large-B-cell lymphoma. |
Q27681982 | The ansamycin antibiotic, rifamycin SV, inhibits BCL6 transcriptional repression and forms a complex with the BCL6-BTB/POZ domain |
Q34313320 | The biology of human lymphoid malignancies revealed by gene expression profiling. |
Q53258385 | The burden of scientific progress: growing inequalities in the delivery of cancer care. |
Q28241767 | The c-Rel transcription factor and B-cell proliferation: a deal with the devil |
Q35122837 | The classification of lymphomas: a new beginning or the end of an era? |
Q46796219 | The contribution of HGAL/GCET2 in immunohistological algorithms: a comparative study in 424 cases of nodal diffuse large B-cell lymphoma |
Q33490384 | The derivation of diagnostic markers of chronic myeloid leukemia progression from microarray data |
Q54643114 | The differential expression of Galectin-1 and Galectin-3 in normal lymphoid tissue and non-Hodgkin's and Hodgkin's lymphomas. |
Q37174123 | The expression of 16 genes related to the cell of origin and immune response predicts survival in elderly patients with diffuse large B-cell lymphoma treated with CHOP and rituximab. |
Q53222182 | The expression of anamorsin in diffuse large B cell lymphoma: possible prognostic biomarker for low IPI patients. |
Q35821001 | The expression of the aurora-A gene and its significance with tumorgenesis in non-Hodgkin's lymphoma |
Q36331576 | The feasibility of gene expression profiling generated in fine-needle aspiration specimens from patients with follicular lymphoma and diffuse large B-cell lymphoma |
Q39566639 | The gene expression profile of unstimulated dendritic cells can be used as a predictor of function. |
Q36280547 | The histological and biological spectrum of diffuse large B-cell lymphoma in the World Health Organization classification |
Q33268949 | The impact of sample imbalance on identifying differentially expressed genes. |
Q77476882 | The microarray way to tailored cancer treatment |
Q37815142 | The molecular background of aggressive B cell lymphomas as a basis for targeted therapy |
Q36939043 | The molecular characterization and clinical management of multiple myeloma in the post-genome era. |
Q34530992 | The molecular classification of multiple myeloma |
Q39986126 | The oral protein-kinase C beta inhibitor enzastaurin (LY317615) suppresses signalling through the AKT pathway, inhibits proliferation and induces apoptosis in multiple myeloma cell lines. |
Q33495401 | The ordering of expression among a few genes can provide simple cancer biomarkers and signal BRCA1 mutations |
Q36120552 | The parameter sensitivity of random forests |
Q34371078 | The pre-B-cell receptor associated protein VpreB3 is a useful diagnostic marker for identifying c-MYC translocated lymphomas |
Q34688223 | The promise of biomarkers in cancer screening and detection |
Q36670881 | The role of angiogenesis in human non-Hodgkin lymphomas |
Q39102576 | The serine-threonine kinase p90RSK is a new target of enzastaurin in follicular lymphoma cells |
Q34047455 | The significance of FOXP1 in diffuse large B-cell lymphoma |
Q48027386 | The therapeutic effect of rituximab on CD5-positive and CD5-negative diffuse large B-cell lymphoma |
Q36964732 | The therapeutic role of targeting protein kinase C in solid and hematologic malignancies |
Q34411134 | The top-scoring 'N' algorithm: a generalized relative expression classification method from small numbers of biomolecules |
Q36169994 | The transcriptome's drugable frequenters |
Q35188517 | The use of genetic microarray analysis to classify and predict prognosis in haematological malignancies. |
Q36773687 | The use of transcriptomic biomarkers for personalized medicine |
Q74308249 | The value of microarray techniques for quantitative gene profiling in molecular diagnostics |
Q53368295 | Tissue microarrays in diffuse large B-cell lymphomas: are they really able to identify distinct prognostic groups in lymphomas of both nodal and extranodal origin? |
Q37385810 | Toward a systems biology approach to investigate cellular networks in normal and malignant B cells |
Q42696739 | Towards Clinically More Relevant Dissection of Patient Heterogeneity via Survival based Bayesian Clustering |
Q35569564 | Towards molecular diagnosis and targeted therapy of lymphoid malignancies |
Q24554209 | Transcriptional analysis of the B cell germinal center reaction |
Q42320170 | Transcriptional mechanism of vascular endothelial growth factor-induced expression of protein kinase CβII in chronic lymphocytic leukaemia cells. |
Q34387585 | Transcriptional profiling of a mouse model for Rett syndrome reveals subtle transcriptional changes in the brain |
Q27939633 | Transcriptional response of Saccharomyces cerevisiae to DNA-damaging agents does not identify the genes that protect against these agents |
Q35129723 | Transducing signals from antigen receptors to nuclear factor kappaB. |
Q31062604 | Translating microarray data for diagnostic testing in childhood leukaemia |
Q27006062 | Treatment of diffuse large B cell lymphoma |
Q28290155 | Tumor cell-mediated induction of the stromal factor stromelysin-3 requires heterotypic cell contact-dependent activation of specific protein kinase C isoforms |
Q33642188 | Tumor-specific and proliferation-specific gene expression typifies murine transgenic B cell lymphomagenesis. |
Q39965971 | Tyrosine kinase inhibition in diffuse large B-cell lymphoma: molecular basis for antitumor activity and drug resistance of dasatinib. |
Q33299950 | Unravelling the hidden heterogeneities of diffuse large B-cell lymphoma based on coupled two-way clustering |
Q37705417 | Unresolved issues in diffuse large B-cell lymphomas |
Q36269919 | Update on lymphoma management: diffuse large B-cell NHL. |
Q38888510 | Upregulation of long noncoding RNA PEG10 associates with poor prognosis in diffuse large B cell lymphoma with facilitating tumorigenicity |
Q47392520 | Use of Expression Analysis to Predict Outcome After Radical Prostatectomy |
Q30992230 | Use of extreme patient samples for outcome prediction from gene expression data. |
Q33196034 | Use of proteomic analysis to monitor responses to biological therapies |
Q35543889 | Using DNA microarrays for diagnostic and prognostic prediction |
Q47971165 | Using Gene Expression Ratios to Predict Outcome Among Patients With Mesothelioma |
Q28386273 | Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data |
Q36743357 | Using the information embedded in the testing sample to break the limits caused by the small sample size in microarray-based classification |
Q37293519 | Utility of subsequent conventional dose chemotherapy in relapsed/refractory transplant-eligible patients with diffuse large B-cell lymphoma failing platinum-based salvage chemotherapy. |
Q36741637 | Utilization of pathway signatures to reveal distinct types of B lymphoma in the Emicro-myc model and human diffuse large B-cell lymphoma |
Q34646755 | Utilization of the Eμ-Myc mouse to model heterogeneity of therapeutic response |
Q47373475 | VEGF121, is predictor for survival in activated B-cell-like diffuse large B-cell lymphoma and is related to an immune response gene signature conserved in cancers |
Q36194645 | Validation of tissue microarray immunohistochemistry staining and interpretation in diffuse large B-cell lymphoma |
Q51897815 | Variable selection in penalized model-based clustering via regularization on grouped parameters. |
Q33369633 | Very Important Pool (VIP) genes--an application for microarray-based molecular signatures |
Q31116629 | Visualization-based cancer microarray data classification analysis |
Q36168226 | Wealth of opportunity - the C1 domain as a target for drug development |
Q34032697 | Weighted Area Under the Receiver Operating Characteristic Curve and Its Application to Gene Selection |
Q37316548 | Why does cytotoxic chemotherapy cure only some cancers? |
Q53362281 | [The genetics of glioma: molecular classification]. |
Q34958884 | c-Myc is an important direct target of Notch1 in T-cell acute lymphoblastic leukemia/lymphoma |
Q36088278 | cDNA microarrays: revolutionary technology for the diagnosis, prognosis, and treatment of cutaneous T-cell lymphoma |
Q36152713 | hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine |
Q35863651 | iRDA: a new filter towards predictive, stable, and enriched candidate genes |
Q36558001 | p53 and Nur77/TR3 - transcription factors that directly target mitochondria for cell death induction |
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