ArticleCurrent genomics2007
Gene expression profiling and its practice in drug development.
Article in Current genomics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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
12 citing papers in PubMed, 46 citations in OpenAlex.
- BuffExDb: web-based tissue-specific gene expression resource for breeding and conservation programmes in Bubalus bubalis.Database : the journal of biological databases and curation · 2025Article
- A Comprehensive Review of the Endometrial Receptivity Array in Euploid Embryo Transfer Cycles.Cureus · 2024Review
- Article
- TCF1 in T cell immunity: a broadened frontier.Nature reviews. Immunology · 2022Review
- Review
- Large-scale labeling and assessment of sex bias in publicly available expression data.BMC bioinformatics · 2021Article
- Drug-Target Interaction Prediction Based on Adversarial Bayesian Personalized Ranking.BioMed research international · 2021Article
- Universal Nature of Drug Treatment Responses in Drug-Tissue-Wide Model-Animal Experiments Using Tensor Decomposition-Based Unsupervised Feature Extraction.Frontiers in genetics · 2020Article
- In silico prediction of novel therapeutic targets using gene-disease association data.Journal of translational medicine · 2017Article
- Toxicogenomics profiling of bone marrow from rats treated with topotecan in combination with oxaliplatin: a mechanistic strategy to inform combination toxicity.Frontiers in genetics · 2015Article
- Will global transcriptome analysis allow the detection of novel prognostic markers in coronary artery disease and heart failure?Current genomics · 2013Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The availability of sequenced genomes of human and many experimental animals necessitated the development of new technologies and powerful computational tools that are capable of exploiting these genomic data and ask intriguing questions about complex nature of biological processes. This gave impetus for developing whole genome approaches that can produce functional information of genes in the form of expression profiles and unscramble the relationships between variation in gene expression and the resulting physiological outcome. These profiles represent genetic fingerprints or catalogue of genes that characterize the cell or tissue being studied and provide a basis from which to begin an investigation of the underlying biology. Among the most powerful and versatile tools are high-density DNA microarrays to analyze the expression patterns of large numbers of genes across different tissues or within the same tissue under a variety of experimental conditions or even between species. The wide spread use of microarray technologies is generating large sets of data that is stimulating the development of better analytical tools so that functions can be predicted for novel genes. In this review, the authors discuss how these profiles are being used at various stages of the drug discovery process and help in the identification of new drug targets, predict the function of novel genes, and understand individual variability in response to drugs.
Indexed as
Identifiers
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.