ReviewMolecular biotechnology2009
Role of in silico tools in gene discovery.
Review in Molecular biotechnology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 17 citations in OpenAlex.
- Identification of Novel Modifier Genes Associated With Pain in Cystic Fibrosis: An In Silico Gene Discovery.Human mutation · 2025Article
- PacBio single-molecule long-read sequencing provides new insights into the complexity of full-length transcripts in oriental river prawn, macrobrachium nipponense.BMC genomics · 2023Article
- Hereditary fructose intolerance: A comprehensive review.World journal of clinical pediatrics · 2022Review
- Teaching genomic counseling: preparing the genetic counseling workforce for the genomic era.Journal of genetic counseling · 2014Article
- BioGraph: unsupervised biomedical knowledge discovery via automated hypothesis generation.Genome biology · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Common complex diseases remain a major health challenge and involve the interaction of multiple genes and environmental factors. Discovering the relevant genes is difficult although it is known that disease risk can originate from the variation of an individual's genome. Application of in silico tools can significantly improve the detection of genes and variation. Data mining and automated tracking of new knowledge facilitate locus mapping. At the gene search stage, in silico prioritization of candidate genes plays an indispensable role in dealing with linked or associated loci. In silico analysis can also differentiate subtle consequences of coding DNA variants and remains the major tool to predict potential effects of non-coding DNA variants on gene transcription and/or pre-mRNA splicing.
Indexed as
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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.