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pivlab · Sep 16, 2024 · 9788491 · 9788491
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 <figure class="figure">
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       <a href="https://doi.org/gr9nx2" class="citation-title">
         The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci
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         Discerning asthma endotypes through comorbidity mapping
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       <a href="https://doi.org/ghxdc9" class="citation-title">
         Exploiting the GTEx resources to decipher the mechanisms at GWAS loci
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         Probabilistic colocalization of genetic variants from complex and molecular traits: promise and limitations
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         Polygenic transcriptome risk scores improve portability of polygenic risk scores across ancestries
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         PhenomeXcan: Mapping the genome to the phenome through the transcriptome
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         DL4papers: a deep learning approach for the automatic interpretation of scientific articles
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         Predicting novel microRNA: a comprehensive comparison of machine learning approaches.
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         Shared and distinct genetic risk factors for childhood-onset and adult-onset asthma: genome-wide and transcriptome-wide studies
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         Integrating predicted transcriptome from multiple tissues improves association detection
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         ukbREST: efficient and streamlined data access for reproducible research in large biobanks
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         Clustermatch: discovering hidden relations in highly diverse kinds of qualitative and quantitative data without standardization
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         Diversity control for improving the analysis of consensus clustering
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       <a href="https://doi.org/f78h5s" class="citation-title">
         A very simple and fast way to access and validate algorithms in reproducible research

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