KMC_2017-dev/index.html at master · MaayanLab/KMC_2017-dev · GitHub

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<!DOCTYPE html>
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    <title>Omics Mining IDG</title>
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            <p id='example_title'>Omics Mining for the Illuminating the Druggable Genome Project</p>
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                <p class='example_single_title'>Target Similarity Matrices</p>
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                    <img id='app_screenshot' src="img/app_screenshot.png">
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                <p class='example_single_description'>The three families of drug targets: GPCRs, ion channels and kinases are clustered by their coexpression based on GTEx or CCLE, or by their coregulation based on ENCODE or ChEA. Under-studied proteins are colored in orange. Such visualization enables the identification of associations between under-studied proteins and their well studied family members.</p>
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              <p class='example_single_title'>Target Functional Predictions</p>
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              <p class='example_single_description'>Co-expression data from all publicly available RNA-seq samples from GEO were used to infer Gene Ontology terms for under-studied proteins. Predictions correctly return known ontology terms as well predict new biological functions for the under-studied protein targets.</p>
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              <p class='example_single_title'>Targets as Biomarkers</p>

              <a href='https://drive.google.com/file/d/0B46LT_Hxo_TtdE1OeUpoTFhiTkk/view'>
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                  <img class='TCGA' id='' src="img/TCGA_analysis.png" >
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              <p class='example_single_description'>Gene expression and patient survival data from TCGA were used to investigate three under-studied kinases identified as part of a cell cycle co-expression cluster. The under-studied kinase PKMYT1 is negatively associated with patient survival of Kidney Renal Clear Cell Carcinoma. See <a href="http://nbviewer.jupyter.org/github/MaayanLab/KMC_2017/blob/master/notebooks/tcga-analysis.ipynb">Jupyter Notebook</a> and <a href="https://drive.google.com/file/d/0B46LT_Hxo_TtdE1OeUpoTFhiTkk/view" target=_blank>summary slides</a>.
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              <p class='example_single_title'>Jupyter Notebooks</p>
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              <p class='example_single_description'>Jupyter notebooks were developed to explore kinase, ion channel, and GPCR clusters identified based on co-expression and co-regulation by transcription fcators. Common biological themes were identified and biological functions were inferred for under-studied potential target proteins.</p>
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        <div class=" footer_text">Developed by the <a class='blue_links' target="_blank"  href="http://icahn.mssm.edu/research/labs/maayan-laboratory">Ma'ayan Lab</a> at the <a class='blue_links' target="_blank"   href="http://icahn.mssm.edu/">Icahn School of Medicine at Mount Sinai</a>  for the <a target="_blank" href="http://commonfund.nih.gov/idg/overview">KMC-IDG</a>  </div>

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