scholarly article | Q13442814 |
P50 | author | Paolo Martini | Q83826287 |
P2093 | author name string | Chiara Romualdi | |
Enrica Calura | |||
Monica Chiogna | |||
P2860 | cites work | Cancer genome landscapes | Q22242276 |
KEGG: kyoto encyclopedia of genes and genomes | Q24515297 | ||
Cytoscape: a software environment for integrated models of biomolecular interaction networks | Q24515682 | ||
Reactome: a knowledgebase of biological pathways | Q24795413 | ||
A Metabolic Immune Checkpoint: Adenosine in Tumor Microenvironment | Q26749571 | ||
Matrix metalloproteinases in stem cell regulation and cancer | Q26825295 | ||
Predictive and prognostic molecular markers for cancer medicine | Q28743108 | ||
Network-based classification of breast cancer metastasis | Q29616384 | ||
Detection of somatic TP53 mutations in tampons of patients with high-grade serous ovarian cancer | Q30301247 | ||
Similarity network fusion for aggregating data types on a genomic scale | Q30742291 | ||
Network-Based Integration of Disparate Omic Data To Identify "Silent Players" in Cancer | Q31032861 | ||
Simultaneous discovery of cancer subtypes and subtype features by molecular data integration. | Q31126286 | ||
simPATHy: a new method for simulating data from perturbed biological PATHways | Q31160214 | ||
Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM. | Q33597322 | ||
More Is Better: Recent Progress in Multi-Omics Data Integration Methods | Q33804425 | ||
Matrix metalloproteinases: molecular aspects of their roles in tumour invasion and metastasis | Q34013787 | ||
Most random gene expression signatures are significantly associated with breast cancer outcome | Q34058091 | ||
Time to recurrence and survival in serous ovarian tumors predicted from integrated genomic profiles | Q34071483 | ||
graphite - a Bioconductor package to convert pathway topology to gene network. | Q34146842 | ||
An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. | Q52602395 | ||
Dysregulation of fibulin-5 and matrix metalloproteases in epithelial ovarian cancer. | Q52629185 | ||
Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application | Q56517003 | ||
Potential Mechanisms Connecting Purine Metabolism and Cancer Therapy | Q57174142 | ||
Multi-omic and multi-view clustering algorithms: review and cancer benchmark | Q57181817 | ||
Resistance to platinum-based chemotherapy is associated with epithelial to mesenchymal transition in epithelial ovarian cancer | Q57202934 | ||
Landscape of genomic alterations in high-grade serous ovarian cancer from exceptional long- and short-term survivors | Q58087981 | ||
Multi-omic tumor data reveal diversity of molecular mechanisms that correlate with survival | Q58115551 | ||
Copy number signatures and mutational processes in ovarian carcinoma | Q61757402 | ||
Perfluorooctanoic acid stimulates ovarian cancer cell migration, invasion via ERK/NF-κB/MMP-2/-9 pathway | Q88647919 | ||
Low levels of ADAM23 expression in epithelial ovarian cancer are associated with poor survival | Q89157053 | ||
Activated EphA2 Processing by MT1-MMP Is Involved in Malignant Transformation of Ovarian Tumours In Vivo | Q89410743 | ||
DIABLO: an integrative approach for identifying key molecular drivers from multi-omics assays | Q91111225 | ||
NEMO: cancer subtyping by integration of partial multi-omic data | Q91277182 | ||
metaGraphite-a new layer of pathway annotation to get metabolite networks | Q91298031 | ||
Pattern discovery and cancer gene identification in integrated cancer genomic data | Q34594856 | ||
Network-based survival analysis reveals subnetwork signatures for predicting outcomes of ovarian cancer treatment | Q34649455 | ||
Personalized sequencing and the future of medicine: discovery, diagnosis and defeat of disease. | Q35107992 | ||
Epigenetic regulation of matrix metalloproteinases and their collagen substrates in cancer | Q35110491 | ||
The clinical relevance of stromal matrix metalloproteinase expression in ovarian cancer | Q35456047 | ||
Efficient Test and Visualization of Multi-Set Intersections | Q36316408 | ||
The Ensembl Variant Effect Predictor | Q36970975 | ||
Bayesian consensus clustering | Q37212910 | ||
TGF-β: friend or foe? The role of TGF-β/SMAD signaling in epigenetic silencing of ovarian cancer and its implication in epigenetic therapy. | Q37798252 | ||
Targeting genetic and epigenetic alterations in the treatment of serous ovarian cancer | Q37964221 | ||
Cancer Systems Biology: a peek into the future of patient care? | Q38184909 | ||
Next generation sequencing: implications in personalized medicine and pharmacogenomics | Q38804924 | ||
A New View into the Regulation of Purine Metabolism: The Purinosome | Q39060886 | ||
Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes | Q40230451 | ||
MethylMix: an R package for identifying DNA methylation-driven genes | Q41069610 | ||
mixOmics: An R package for 'omics feature selection and multiple data integration | Q45846807 | ||
Integrating Clinical and Multiple Omics Data for Prognostic Assessment across Human Cancers. | Q45943258 | ||
Targeting immunosuppressive adenosine in cancer | Q46140918 | ||
A novel approach for data integration and disease subtyping | Q47234937 | ||
Deep Learning based multi-omics integration robustly predicts survival in liver cancer. | Q47855807 | ||
Whole-genome characterization of chemoresistant ovarian cancer | Q50272478 | ||
P275 | copyright license | Creative Commons Attribution-NonCommercial 4.0 International | Q34179348 |
P6216 | copyright status | copyrighted | Q50423863 |
P433 | issue | 14 | |
P921 | main subject | pathway analysis | Q25303877 |
P304 | page(s) | e80 | |
P577 | publication date | 2019-08-01 | |
P1433 | published in | Nucleic Acids Research | Q135122 |
P1476 | title | MOSClip: multi-omic and survival pathway analysis for the identification of survival associated gene and modules | |
P478 | volume | 47 |
Q91328454 | Aggregated network centrality shows non-random structure of genomic and proteomic networks | cites work | P2860 |
Search more.