mity: A highly sensitive mitochondrial variant analysis pipeline for whole genome sequencing data
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Updated
Jun 7, 2024 - Python
mity: A highly sensitive mitochondrial variant analysis pipeline for whole genome sequencing data
An Artificial Neural Network-based discriminator for validating clinically significant genomic variants
Text mining cancer biomarkers for the CIVIC database
Patient-Specific Modeling in Python
Subclassification of disease states based on the intersection of literature and expression
Services and guidelines for normalizing drug and other therapy terms
Code for paper Multiomics dynamic learning enables personalized diagnosis and prognosis for pan-cancer and cancer-subtypes
TractLearn is a Manifold Learning Toolbox for precision medicine. The first application is for Diffusion-Weighted MRI quantitative analysis.
Services and guidelines for normalizing disease terms
Easy to use web interface for biologists to look for genetic variants and understand their deleteriousness using DITTO scores.
Neural text summarization for document retrieval
Precision Medicine Target-Drug Selection in Cancer
Services and guidelines for normalizing genes
Computational phenotyping used in the paper "Explainable AI on H&E Predicts Docetaxel Benefit for High-Risk Localized Prostate Cancer in RTOG 0521"
Code to accompany the paper: ”ProteinNetworkSight efficiently transforms co-expressed protein lists into interactive networks and offers suggestions for their modifications”
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