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  2. Luda Diatchenko - Wikipedia

    en.wikipedia.org/wiki/Luda_Diatchenko

    Diatchenko also believes in and contributes to open science to advance our understanding of the molecular mechanisms of pain. Her lab's Human Pain Genetics Database (HPGdb) summarizes all extant data on the genetic contributors of pain and the Transcriptomics Pain Signatures Database (PSGS) summarizes all available data on genome-wide ...

  3. Jeffrey Mogil - Wikipedia

    en.wikipedia.org/wiki/Jeffrey_Mogil

    He is known for his work in the genetics of pain, [2] for being among the first scientists to demonstrate sex differences in pain perception, [3] and for identifying previously unknown factors and confounds that affect the integrity of contemporary pain research. [4] He has an h-index of 100. [5]

  4. Tail flick test - Wikipedia

    en.wikipedia.org/wiki/Tail_flick_test

    A mouse of one genetic line may be more or less tolerant of pain than a mouse of another genetic line. Also, a mouse of one genetic line may experience a higher or lower effectiveness of an analgesic than a mouse of another genetic line. Using this test, researchers can also begin to identify genes that play a role in pain sensation.

  5. Gene Disease Database - Wikipedia

    en.wikipedia.org/wiki/Gene_Disease_Database

    In bioinformatics, a Gene Disease Database is a systematized collection of data, typically structured to model aspects of reality, in a way to comprehend the underlying mechanisms of complex diseases, by understanding multiple composite interactions between phenotype-genotype relationships and gene-disease mechanisms. [1]

  6. GeneCards - Wikipedia

    en.wikipedia.org/wiki/GeneCards

    [1] [5] [6] The GeneCards database provides access to free Web resources about more than 350,000 known and predicted human genes, integrated from >150 data resources, such as HGNC, Ensembl, and NCBI. The core gene list is based on NCBI, Ensembl and approved gene symbols published by the HUGO Gene Nomenclature Committee (HGNC).

  7. KEGG - Wikipedia

    en.wikipedia.org/wiki/KEGG

    KEGG (Kyoto Encyclopedia of Genes and Genomes) is a collection of databases dealing with genomes, biological pathways, diseases, drugs, and chemical substances.KEGG is utilized for bioinformatics research and education, including data analysis in genomics, metagenomics, metabolomics and other omics studies, modeling and simulation in systems biology, and translational research in drug development.

  8. Why Am I Snacking So Much? (& How to Stop) - AOL

    www.aol.com/why-am-snacking-much-stop-125800077.html

    If you’re feeling hunger cues (e.g., a rumbling stomach), go ahead and grab that snack, guilt-free! But if you’re reaching for a snack because of another trigger, consider a snack-free way to ...

  9. DisGeNET - Wikipedia

    en.wikipedia.org/wiki/DisGeNET

    The DisGeNET database integrates over 400 000 associations between > 17 000 genes and > 14 000 diseases from human to animal model expert curated databases with text mined GDAs from MEDLINE using a NLP-based approach. [4] The highlights of DisGeNET are the data integration, standardisation and a fine-grained tracking of the provenance information.