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@AlexandrovLab
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rvangara/README.md

Dr. Raviteja Vangara is currently a Postdoctoral Researcher in the Alexandrov lab at the Department of Cellular and Molecular Medicine, UCSD. His current research includes utilizing state-of-art machine learning approaches for mutational scignature analysis for human cancer.

Prior to this, he was a researcher at Theoretical Division, Los Alamos National Laboratory where he worked on various scientific applications that utilize unsupervised machine learning techniques which involve graphical clustering methods, non-negative matrix and tensor factorization techniques for pattern recognition, and latent feature extraction. At LANL, Dr. Vangara was part of a 2021 R&D award winning team, Smart Tensors, that released several open source softwares that utilizes scalable distributed computing methods for high-performance computing scientific applications.

Dr. Vangara received Ph.D. with distinction in 2019 for his work on Coulumbic and non Coulumbic effects of Electric Double Layers and M.S in 2017 from the Petsev lab, Department of Chemical and Biological Engineering, The University of New Mexico.

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  1. AlexandrovLab/SigProfilerExtractor AlexandrovLab/SigProfilerExtractor Public

    SigProfilerExtractor allows de novo extraction of mutational signatures from data generated in a matrix format. The tool identifies the number of operative mutational signatures, their activities i…

    Python 148 50

  2. AlexandrovLab/SigProfilerAssignment AlexandrovLab/SigProfilerAssignment Public

    Assignment of known mutational signatures to individual samples and individual somatic mutations

    Python 39 9

  3. AlexandrovLab/SigProfilerMatrixGenerator AlexandrovLab/SigProfilerMatrixGenerator Public

    SigProfilerMatrixGenerator creates mutational matrices for all types of somatic mutations. It allows downsizing the generated mutations only to parts for the genome (e.g., exome or a custom BED fil…

    Python 96 33

  4. AlexandrovLab/SigProfilerPlotting AlexandrovLab/SigProfilerPlotting Public

    SigProfilerPlotting provides a standard tool for displaying all types of mutational signatures as well as all types of mutational patterns in cancer genomes. The tool seamlessly integrates with oth…

    Python 45 13

  5. pyDNMFk pyDNMFk Public

    Forked from lanl/pyDNMFk

    Python Distributed Non Negative Matrix Factorization with custom clustering

    Python 1

  6. DnMFk DnMFk Public

    Forked from lanl/DnMFk

    A C++ framework of Distributed Non-Negative Matrix Factorization implementation to find Latent Dimensionality in Big Data

    C++ 1