All Stories

  1. Whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer
  2. Orchestrating a community-developed computational workshop and accompanying training materials
  3. Integrative cancer pharmacogenomics to establish drug mechanism of action: drug repurposing
  4. Revisiting inconsistency in large pharmacogenomic studies
  5. MetaGxData: Breast and Ovarian Clinically Annotated Transcriptomics Datasets
  6. Assessment of pharmacogenomic agreement
  7. Assessment of pharmacogenomic agreement
  8. MM2S: personalized diagnosis of medulloblastoma patients and model systems
  9. Integrative pharmacogenomics to infer large-scale drug taxonomy
  10. PharmacoGx: an R package for analysis of large pharmacogenomic datasets
  11. Genefu: an R/Bioconductor package for computation of gene expression-based signatures in breast cancer
  12. Association of Treatment with Carvedilol, Bisoprolol and Metoprolol on the Risk of Mortality and Hospital Admission Among Older Adults with Heart Failure
  13. Public data and open source tools for multi-assay genomic investigation of disease
  14. Using Cell line and Patient samples to improve Drug Response Prediction
  15. Revisiting inconsistency in large pharmacogenomic studies
  16. Personalized diagnosis of medulloblastoma subtypes across patients and model systems
  17. Abstract 5297: Chromosomal instability as a prognostic marker in cervical cancer
  18. Characterization of Conserved Toxicogenomic Responses in Chemically Exposed Hepatocytes across Species and Platforms
  19. Extensive rewiring of epithelial-stromal co-expression networks in breast cancer
  20. Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer
  21. Using shRNA experiments to validate gene regulatory networks
  22. ABC: a tool to identify SNVs causing allele-specific transcription factor binding from ChIP-Seq experiments: Fig. 1.
  23. Chromosomal instability as a prognostic marker in cervical cancer
  24. A network model for angiogenesis in ovarian cancer
  25. Test set bias affects reproducibility of gene signatures
  26. Identification of a microRNA signature associated with risk of distant metastasis in nasopharyngeal carcinoma
  27. CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma
  28. APOBEC3B expression in breast cancer reflects cellular proliferation, while a deletion polymorphism is associated with immune activation
  29. ZNF143 provides sequence specificity to secure chromatin interactions at gene promoters
  30. Medulloblastoma subgroups remain stable across primary and metastatic compartments
  31. Quantitative Assessment and Validation of Network
  32. Untangling statistical and biological models to understand network inference: the need for a genomics network ontology
  33. Gene regulatory networks and their applications: understanding biological and medical problems in terms of networks
  34. Corrigendum: Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
  35. Quantitative assessment and validation of network inference methods in bioinformatics
  36. Robust Radiomics Feature Quantification Using Semiautomatic Volumetric Segmentation
  37. Enhancing Reproducibility in Cancer Drug Screening: How Do We Move Forward?
  38. Relevance of different prior knowledge sources for inferring gene interaction networks
  39. Avoiding test set bias with rank-based prediction
  40. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
  41. Integration of mRNA Expression Profile, Copy Number Alterations, and microRNA Expression Levels in Breast Cancer to Improve Grade Definition
  42. Inference and validation of predictive gene networks from biomedical literature and gene expression data
  43. Comparative Meta-analysis of Prognostic Gene Signatures for Late-Stage Ovarian Cancer
  44. Importance of collection in gene set enrichment analysis of drug response in cancer cell lines
  45. Similarity network fusion for aggregating data types on a genomic scale
  46. The gene regulatory network for breast cancer: integrated regulatory landscape of cancer hallmarks
  47. Functional and genetic analysis of the colon cancer network
  48. Exploiting high-throughput cell line drug screening studies to identify candidate therapeutic agents in head and neck cancer
  49. Transfer of clinically relevant gene expression signatures in breast cancer: from Affymetrix microarray to Illumina RNA-Sequencing technology
  50. Chapter 7: On the Integration of Prior Knowledge in the Inference of Regulatory Networks
  51. Novel Effects of Chromosome Y on Cardiac Regulation, Chromatin Remodeling, and Neonatal Programming in Male Mice
  52. Genome-wide gene expression profiling to predict resistance to anthracyclines in breast cancer patients
  53. Inconsistency in large pharmacogenomic studies
  54. mRMRe: an R package for parallelized mRMR ensemble feature selection
  55. Comparison and validation of genomic predictors for anticancer drug sensitivity
  56. CD4+ follicular helper T cell infiltration predicts breast cancer survival
  57. curatedOvarianData: clinically annotated data for the ovarian cancer transcriptome
  58. Stem Cell-Like Gene Expression in Ovarian Cancer Predicts Type II Subtype and Prognosis
  59. Significance Analysis of Prognostic Signatures
  60. RamiGO: an R/Bioconductor package providing an AmiGO Visualize interface
  61. Network statistics of genetically-driven gene co-expression modules in mouse crosses
  62. Estrogen receptor negative/progesterone receptor positive breast cancer is not a reproducible subtype
  63. Proliferation and estrogen signaling can distinguish patients at risk for early versus late relapse among estrogen receptor positive breast cancers
  64. MicroRNA paraffin-based studies in osteosarcoma reveal reproducible independent prognostic profiles at 14q32
  65. Abstract P3-04-10: Comparison between RNA-Seq and Affymetrix gene expression data
  66. Angiogenic mRNA and microRNA Gene Expression Signature Predicts a Novel Subtype of Serous Ovarian Cancer
  67. Analysis of Array Data and Clinical Validation of Array-Based Assays
  68. Analysis of Array Data and Clinical Validation of Array-Based Assays
  69. PD03-10: Gene Modules and Response to Neoadjuvant Chemotherapy in Breast Cancer: A Meta-Analysis.
  70. DNA methylation profiling reveals a predominant immune component in breast cancers
  71. survcomp: an R/Bioconductor package for performance assessment and comparison of survival models
  72. Global MicroRNA Expression Profiling Identifies MiR-210 Associated with Tumor Proliferation, Invasion and Poor Clinical Outcome in Breast Cancer
  73. Multifactorial Approach to Predicting Resistance to Anthracyclines
  74. Multiple-input multiple-output causal strategies for gene selection
  75. Consistent metagenes from cancer expression profiles yield agent specific predictors of chemotherapy response
  76. Minimising Immunohistochemical False Negative ER Classification Using a Complementary 23 Gene Expression Signature of ER Status
  77. Time to move forward from “first-generation” prognostic gene signatures in early breast cancer
  78. Classification Models for Breast Cancer Molecular Subtyping: What is the Best Candidate for a Translation into Clinic?
  79. Long-term In Vitro Treatment of Human Glioblastoma Cells with Temozolomide Increases Resistance In Vivo through Up-regulation of GLUT Transporter and Aldo-Keto Reductase Enzyme AKR1C Expression
  80. Low CD10 mRNA Expression Identifies High-Risk Ductal Carcinoma In Situ (DCIS)
  81. Abstract 4895: Component of the gene silencing machinery: SMCX/JARID1C a new prognostic marker for breast cancer
  82. Assessment of an RNA interference screen-derived mitotic and ceramide pathway metagene as a predictor of response to neoadjuvant paclitaxel for primary triple-negative breast cancer: a retrospective analysis of five clinical trials
  83. Amplification of LAPTM4B and YWHAZ contributes to chemotherapy resistance and recurrence of breast cancer
  84. A fuzzy gene expression-based computational approach improves breast cancer prognostication
  85. Long-term Temozolomide Treatment Induces Marked Amino Metabolism Modifications and an Increase in TMZ Sensitivity in Hs683 Oligodendroglioma Cells
  86. A Meta-Analysis of Gene Expression Profiling Studies Identifies Clinically Relevant Oncogenic Pathways in Basal-Like Breast Cancer.:
  87. Limited Clinical Utility of Prognostic Gene Expression Profiles in Grade 3 Node-Negative Early Stage Breast Cancer.
  88. Decreased CD10 Expression Is Associated with a Higher Risk of Relapse in Ductal Carcinoma In Situ (DCIS).
  89. Early Assessment of Proliferation by the Genomic Grade Index (GGI) Predicts Response to Neo-Adjuvant Letrozole.
  90. Molecular profiling of CD3-CD4+ T cells from patients with the lymphocytic variant of hypereosinophilic syndrome reveals targeting of growth control pathways
  91. Galectin 1 Proangiogenic and Promigratory Effects in the Hs683 Oligodendroglioma Model Are Partly Mediated through the Control of BEX2 Expression
  92. Gene expression profiling reveals differences in microenvironment interaction between patients with chronic lymphocytic leukemia expressing high versus low ZAP70 mRNA
  93. microRNA-29c and microRNA-223 down-regulation has in vivo significance in chronic lymphocytic leukemia and improves disease risk stratification
  94. Gene expression profiling identifies activated growth factor signaling in poor prognosis (Luminal-B) estrogen receptor positive breast cancer
  95. Temozolomide displays antimigratory effects in human glioblastoma cells mediated through neuregulin-1 down-regulation
  96. Improvement of the clinical applicability of the Genomic Grade Index through a qRT-PCR test performed on frozen and formalin-fixed paraffin-embedded tissues
  97. The Gene expression Grade Index: a potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 1–98 trial
  98. Biological Processes Associated with Breast Cancer Clinical Outcome Depend on the Molecular Subtypes
  99. A comparative study of survival models for breast cancer prognostication based on microarray data: does a single gene beat them all?
  100. UNBS5162, a Novel Naphthalimide That Decreases CXCL Chemokine Expression in Experimental Prostate Cancers
  101. Evidence of galectin-1 involvement in glioma chemoresistance☆
  102. Knocking Down Galectin 1 in Human Hs683 Glioblastoma Cells Impairs Both Angiogenesis and Endoplasmic Reticulum Stress Responses
  103. Molecular qRT-PCR grade index: a new tool for breast cancer (BC) patient grading improvement
  104. Farnesoid X receptor (FXR) status complements the evaluation of estrogen receptor alpha (ER) in breast cancer (BC) patients and predicts benefit from tamoxifen
  105. OC3. Farnesoid X receptor (FXR): A new marker for the prediction of bone metastases in breast cancer
  106. Meta-analysis of gene-expression profiles in breast cancer: toward a unified understanding of breast cancer sub-typing and prognosis signatures
  107. Comparison of prognostic gene expression signatures for breast cancer
  108. Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen
  109. Quantification of ZAP70 mRNA in B Cells by Real-Time PCR Is a Powerful Prognostic Factor in Chronic Lymphocytic Leukemia
  110. In Reply
  111. 4-IBP, a σ1 Receptor Agonist, Decreases the Migration of Human Cancer Cells, Including Glioblastoma Cells, In Vitro and Sensitizes Them In Vitro and In Vivo to Cytotoxic Insults of Proapoptotic and Proautophagic Drugs
  112. Is genomic grading killing histological grading?
  113. Gene regulation by phorbol 12-myristate 13-acetate in MCF-7 and MDA-MB-231, two breast cancer cell lines exhibiting highly different phenotypes
  114. Computational Intelligence in Clinical Oncology: Lessons Learned from an Analysis of a Clinical Study