scholarly article | Q13442814 |
P356 | DOI | 10.1038/NRC2036 |
P8608 | Fatcat ID | release_geazxfobsnelbgsedeqgb6d3e4 |
P698 | PubMed publication ID | 17167517 |
P5875 | ResearchGate publication ID | 6631510 |
P50 | author | Gary D. Bader | Q37393655 |
Pingzhao Hu | Q39652071 | ||
Andrew Emili | Q64126987 | ||
P2093 | author name string | Dennis A Wigle | |
P2860 | cites work | The Hallmarks of Cancer | Q221226 |
A physical and functional map of the human TNF-alpha/NF-kappa B signal transduction pathway | Q21735927 | ||
Towards a proteome-scale map of the human protein–protein interaction network | Q21735930 | ||
The Shwachman-Diamond SBDS protein localizes to the nucleolus | Q24300969 | ||
Core transcriptional regulatory circuitry in human embryonic stem cells | Q24322016 | ||
A human protein-protein interaction network: a resource for annotating the proteome | Q24324450 | ||
Prediction of functional modules based on comparative genome analysis and Gene Ontology application | Q24527323 | ||
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs | Q24545170 | ||
DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions | Q24548456 | ||
IntAct: an open source molecular interaction database | Q24600582 | ||
Stromal effects on mammary gland development and breast cancer | Q24645558 | ||
A census of human cancer genes | Q24647081 | ||
Global topological features of cancer proteins in the human interactome | Q24672981 | ||
STRING: a database of predicted functional associations between proteins | Q24681946 | ||
Clustering proteins from interaction networks for the prediction of cellular functions | Q24794683 | ||
The functional landscape of mouse gene expression | Q24794985 | ||
Identifying protein function--a call for community action | Q24800079 | ||
AVID: an integrative framework for discovering functional relationships among proteins | Q24813007 | ||
BABELOMICS: a suite of web tools for functional annotation and analysis of groups of genes in high-throughput experiments. | Q24813075 | ||
Pathguide: a pathway resource list | Q25256662 | ||
The KEGG resource for deciphering the genome | Q27860687 | ||
Gene expression profiling predicts clinical outcome of breast cancer | Q27860732 | ||
The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003 | Q27860747 | ||
Network biology: understanding the cell's functional organization | Q27861027 | ||
The Shwachman-Bodian-Diamond syndrome protein family is involved in RNA metabolism | Q27933622 | ||
Large-scale prediction of Saccharomyces cerevisiae gene function using overlapping transcriptional clusters | Q27936646 | ||
Assembly of Cell Regulatory Systems Through Protein Interaction Domains | Q28155799 | ||
Development of human protein reference database as an initial platform for approaching systems biology in humans | Q28206967 | ||
High-throughput mapping of a dynamic signaling network in mammalian cells | Q28239249 | ||
Cancer genes and the pathways they control | Q28275089 | ||
Human homolog of patched, a candidate gene for the basal cell nevus syndrome | Q28281033 | ||
Cell-cycle checkpoints and cancer | Q28293996 | ||
Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling | Q28588350 | ||
BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks | Q29547427 | ||
A gene-coexpression network for global discovery of conserved genetic modules | Q29614451 | ||
MIPS: a database for genomes and protein sequences | Q29614501 | ||
BIND: the Biomolecular Interaction Network Database | Q29616859 | ||
A general framework for weighted gene co-expression network analysis | Q29617580 | ||
MINT: a Molecular INTeraction database | Q29618559 | ||
GenMAPP, a new tool for viewing and analyzing microarray data on biological pathways | Q29618720 | ||
A network of protein-protein interactions in yeast | Q30004209 | ||
Complete cloning of the duchenne muscular dystrophy (DMD) cDNA and preliminary genomic organization of the DMD gene in normal and affected individuals | Q30050310 | ||
Relating whole-genome expression data with protein-protein interactions | Q30669147 | ||
Learning gene functional classifications from multiple data types | Q30693068 | ||
Systematic learning of gene functional classes from DNA array expression data by using multilayer perceptrons | Q30745866 | ||
A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae). | Q30806988 | ||
Predicting protein function from protein/protein interaction data: a probabilistic approach | Q30811144 | ||
Finding function: evaluation methods for functional genomic data | Q30820459 | ||
Global protein function annotation through mining genome-scale data in yeast Saccharomyces cerevisiae | Q30977956 | ||
Chronic myeloid leukemia | Q33603077 | ||
Mutations in SBDS are associated with Shwachman-Diamond syndrome | Q33963285 | ||
Intrinsic errors in genome annotation | Q34085839 | ||
The genetics and genomics of cancer | Q34180336 | ||
WormBase: a multi-species resource for nematode biology and genomics | Q34284591 | ||
Mutations of the SBDS gene are present in most patients with Shwachman-Diamond syndrome | Q34337305 | ||
Online predicted human interaction database | Q34385609 | ||
Biological networks | Q35119735 | ||
Sequence-based cancer genomics: progress, lessons and opportunities | Q35140822 | ||
Cancer susceptibility in the mouse: genetics, biology and implications for human cancer | Q35209979 | ||
Analyzing protein function on a genomic scale: the importance of gold-standard positives and negatives for network prediction | Q35903266 | ||
Systems biology for cancer | Q35988686 | ||
Interactome modeling | Q36069223 | ||
Integrative analysis of the cancer transcriptome | Q36141641 | ||
From signatures to models: understanding cancer using microarrays | Q36141647 | ||
Forensic genetics and ethical, legal and social implications beyond the clinic | Q36503211 | ||
Graph-based methods for analysing networks in cell biology | Q36552759 | ||
Whole-genome annotation by using evidence integration in functional-linkage networks | Q36852724 | ||
Hierarchical multi-label prediction of gene function | Q38519155 | ||
Genome-wide screening for complete genetic loss in prostate cancer by comparative hybridization onto cDNA microarrays | Q40667885 | ||
Whole-proteome prediction of protein function via graph-theoretic analysis of interaction maps | Q42659943 | ||
Exploiting indirect neighbours and topological weight to predict protein function from protein-protein interactions | Q42683787 | ||
Systematic identification of functional orthologs based on protein network comparison | Q43252162 | ||
Detection of functional modules from protein interaction networks. | Q47285412 | ||
Global protein function prediction from protein-protein interaction networks | Q47921995 | ||
Learning kernels from biological networks by maximizing entropy | Q48533625 | ||
Edge-count probabilities for the identification of local protein communities and their organization | Q57385264 | ||
Protein function prediction using the Protein Link EXplorer (PLEX) | Q59447190 | ||
High frequency of fusion transcripts of exon 11 and exon 4/5 in AF-4 gene is observed in cord blood, as well as leukemic cells from infant leukemia patients with t(4;11)(q21;q23) | Q77299338 | ||
Integrated global profiling of cancer | Q80402791 | ||
A probabilistic functional network of yeast genes | Q81067438 | ||
CFinder: locating cliques and overlapping modules in biological networks | Q82534265 | ||
??? | Q59148640 | ||
P433 | issue | 1 | |
P407 | language of work or name | English | Q1860 |
P304 | page(s) | 23-34 | |
P577 | publication date | 2006-12-14 | |
P13046 | publication type of scholarly work | review article | Q7318358 |
P1433 | published in | Nature Reviews Cancer | Q641657 |
P1476 | title | Computational prediction of cancer-gene function | |
P478 | volume | 7 |
Q34761291 | A Role of TGFß1 Dependent 14-3-3σ Phosphorylation at Ser69 and Ser74 in the Regulation of Gene Transcription, Stemness and Radioresistance |
Q35990752 | A Topology-Based Metric for Measuring Term Similarity in the Gene Ontology |
Q38442252 | A machine-learned computational functional genomics-based approach to drug classification |
Q60915322 | A model to predict the function of hypothetical proteins through a nine-point classification scoring schema |
Q51744595 | Adhesion, proliferation, and apoptosis in different molecular portraits of breast cancer treated with silver nanoparticles and its pathway-network analysis |
Q41356904 | An improved hypergeometric probability method for identification of functionally linked proteins using phylogenetic profiles |
Q28476427 | Analysis of kinase gene expression patterns across 5681 human tissue samples reveals functional genomic taxonomy of the kinome |
Q36976745 | Annotating proteins with generalized functional linkages |
Q35214509 | Biochemical functional predictions for protein structures of unknown or uncertain function |
Q37153533 | Cancer as a system failure |
Q26851744 | Candidate gene association studies: a comprehensive guide to useful in silico tools |
Q40523625 | Computational functional genomics based analysis of pain-relevant micro-RNAs. |
Q30989707 | Development of Bioinformatics Pipeline for Analyzing Clinical Pediatric NGS Data. |
Q30493496 | Extracting consistent knowledge from highly inconsistent cancer gene data sources |
Q38487175 | Functional genomics suggest neurogenesis in the adult human olfactory bulb |
Q28078745 | Future paradigms for precision oncology |
Q37468623 | Gene expression profiling for the investigation of soft tissue sarcoma pathogenesis and the identification of diagnostic, prognostic, and predictive biomarkers |
Q37754827 | Immunoinformatics: an overview of computational tools and techniques for understanding immune function |
Q38022502 | Inferring gene functions through dissection of relevance networks: interleaving the intra- and inter-species views |
Q36393263 | Inflammation and breast cancer. Inflammatory component of mammary carcinogenesis in ErbB2 transgenic mice |
Q28744621 | Integrative computational biology for cancer research |
Q33734760 | Involvement of Chromatin Remodeling Genes and the Rho GTPases RhoB and CDC42 in Ovarian Clear Cell Carcinoma. |
Q38089257 | Lost in translation: five grand challenges for proteomic biomarker discovery |
Q58110141 | Machine Learning in Human Olfactory Research. |
Q82774858 | Nine steps to proteomic wisdom: A practical guide to using protein‐protein interaction networks and molecular pathways as a framework for interpreting disease proteomic profiles |
Q34059056 | Parameter adaptations during phenotype transitions in progressive diseases. |
Q28535030 | Parameter trajectory analysis to identify treatment effects of pharmacological interventions |
Q30481763 | Predicting cancer involvement of genes from heterogeneous data |
Q37014089 | Predicting protein function from sequence and structure |
Q42822627 | Prioritization of candidate cancer genes--an aid to oncogenomic studies |
Q31074800 | Process Pharmacology: A Pharmacological Data Science Approach to Drug Development and Therapy |
Q45945654 | Protein complexes, big data, machine learning and integrative proteomics: lessons learned over a decade of systematic analysis of protein interaction networks. |
Q33751211 | RIDDLE: reflective diffusion and local extension reveal functional associations for unannotated gene sets via proximity in a gene network |
Q43811083 | Sequential linear neighborhood propagation for semi-supervised protein function prediction |
Q21145302 | Systematically differentiating functions for alternatively spliced isoforms through integrating RNA-seq data |
Q36841980 | The fibromatosis signature defines a robust stromal response in breast carcinoma |
Q33417875 | Topological and organizational properties of the products of house-keeping and tissue-specific genes in protein-protein interaction networks |
Q33847103 | Unveiling protein functions through the dynamics of the interaction network |
Q30670257 | Using biological pathway data with paxtools |
Q39096958 | What do all the (human) micro-RNAs do? |
Search more.