ReviewHuman genetics2011
Integrative computational biology for cancer research.
Review in Human genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prioritizing therapeutics for lung cancer: an integrative meta-analysis of cancer gene signatures and chemogenomic data.PLoS computational biology · 2015Pooled it
- Curcumin-like Compound Inhibits Proliferation of Adenocarcinoma Cells by Inducing Cell Cycle Arrest and Senescence.Pharmaceuticals (Basel, Switzerland) · 2025Article
- A gene regulatory network approach harmonizes genetic and epigenetic signals and reveals repurposable drug candidates for multiple sclerosis.Human molecular genetics · 2023Article
- Targeting the DNA Damage Response Machinery for Lung Cancer Treatment.Pharmaceuticals (Basel, Switzerland) · 2022Review
- A multiple network-based bioinformatics pipeline for the study of molecular mechanisms in oncological diseases for personalized medicine.Briefings in bioinformatics · 2021Article
- Ubiquitination-Related miRNA-mRNA Interaction Is a Potential Mechanism in the Progression of Retinoblastoma.Investigative ophthalmology & visual science · 2021Article
- DNA repair pathways and their roles in drug resistance for lung adenocarcinoma.Molecular biology reports · 2021Review
- Identification of prognostic biomarkers in colorectal cancer using a long non-coding RNA-mediated competitive endogenous RNA network.Oncology letters · 2019Article
- Article
- Identification of Pharmacologically Tractable Protein Complexes in Cancer Using the R-Based Network Clustering and Visualization Program MCODER.BioMed research international · 2017Article
- Multiple signatures of a disease in potential biomarker space: Getting the signatures consensus and identification of novel biomarkers.BMC genomics · 2015Article
- Integrative analysis reveals disease-associated genes and biomarkers for prostate cancer progression.BMC medical genomics · 2014Article
- Mining breast cancer genes with a network based noise-tolerant approach.BMC systems biology · 2013Article
- Interlaboratory reproducibility of large-scale human protein-complex analysis by standardized AP-MS.Nature methods · 2013Article
- NetwoRx: connecting drugs to networks and phenotypes in Saccharomyces cerevisiae.Nucleic acids research · 2013Article
- Infrared spectroscopy and microscopy in cancer research and diagnosis.American journal of cancer research · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Over the past two decades, high-throughput (HTP) technologies such as microarrays and mass spectrometry have fundamentally changed clinical cancer research. They have revealed novel molecular markers of cancer subtypes, metastasis, and drug sensitivity and resistance. Some have been translated into the clinic as tools for early disease diagnosis, prognosis, and individualized treatment and response monitoring. Despite these successes, many challenges remain: HTP platforms are often noisy and suffer from false positives and false negatives; optimal analysis and successful validation require complex workflows; and great volumes of data are accumulating at a rapid pace. Here we discuss these challenges, and show how integrative computational biology can help diminish them by creating new software tools, analytical methods, and data standards.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.