ReviewHuman genetics2013
Hunting human disease genes: lessons from the past, challenges for the future.
Review in Human genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed, 82 citations in OpenAlex.
- Influence of multi-species data on gene-disease associations in substance use disorder using random walk with restart models.PloS one · 2025Article
- High diagnostic rate of trio exome sequencing in consanguineous families with neurogenetic diseases.Brain : a journal of neurology · 2022Article
- The Biological Significance of Multi-copy Regions and Their Impact on Variant Discovery.Genomics, proteomics & bioinformatics · 2020Article
- MaveQuest: a web resource for planning experimental tests of human variant effects.Bioinformatics (Oxford, England) · 2020Article
- Human gene and disease associations for clinical-genomics and precision medicine research.Clinical and translational medicine · 2020Article
- Debutant iOS app and gene-disease complexities in clinical genomics and precision medicine.Clinical and translational medicine · 2019Article
- Disease Pathway Cut for Multi-Target drugs.BMC bioinformatics · 2019Article
- Replication of a rare risk haplotype on 1p36.33 for autism spectrum disorder.Human genetics · 2018Article
- Big Data Analytics for Genomic Medicine.International journal of molecular sciences · 2017Review
- Quantifying prion disease penetrance using large population control cohorts.Science translational medicine · 2016Article
- Challenges of Identifying Clinically Actionable Genetic Variants for Precision Medicine.Journal of healthcare engineering · 2016Review
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- Article
- Mutation in CEP63 co-segregating with developmental dyslexia in a Swedish family.Human genetics · 2015Article
- The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities.American journal of human genetics · 2015Review
- SLC transporters as therapeutic targets: emerging opportunities.Nature reviews. Drug discovery · 2015Review
- Review
- Exome sequencing identifies DLG1 as a novel gene for potential susceptibility to Crohn's disease in a Chinese family study.PloS one · 2014Article
- From an orphan disease to a generalized molecular mechanism: PTPN11 loss-of-function mutations in the pathogenesis of metachondromatosis.Rare diseases (Austin, Tex.) · 2013Article
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 at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The concept that a specific alteration in an individual's DNA can result in disease is central to our notion of molecular medicine. The molecular basis of more than 3,500 Mendelian disorders has now been identified. In contrast, the identification of genes for common disease has been much more challenging. We discuss historical and contemporary approaches to disease gene identification, focusing on novel opportunities such as the use of population extremes and the identification of rare variants. While our ability to sequence DNA has advanced dramatically, assigning function to a given sequence change remains a major challenge, highlighting the need for both bioinformatics and functional approaches to appropriately interpret these data. We review progress in mapping and identifying human disease genes and discuss future challenges and opportunities for the field.
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.