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Achievements

Achievement: Pull Sharkx2Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: StarstruckAchievement: QuickdrawAchievement: Arctic Code Vault Contributor

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jolespin/README.md

Hello there 👋

Josh L. Espinoza, Ph.D

About Me:

I am an interdisciplinary computational research scientist investigating topics in microbial ecology, systems biology, and natural product discovery. My expertise in multi-omics (primarily (meta)genomics), pipeline development, and machine learning/artificial intelligence has been validated by an extensive track record of >30 peer-reviewed publications (10 of which I am lead author) with over 2000 citations. My career objective is to use cutting-edge computational approaches to translate microbiome research into biotechnology and, thus, increase value on sustaining natural environmental systems.

Affiliations:

  • NewAtlantis Labs - Principal Bioinformatics Scientist
  • J. Craig Venter Institute - Visiting Scientist

Education:

  • Ph.D in Biotechnology, Durban University of Technology (2022). (Dissertation) doi:10.51415/10321/4701
  • M.Sc in Bioinformatics, University of California Santa Cruz (2016)
  • B.Sc in Cellular and Molecular Biology, San Diego State University (2013)

Peer-Reviewed Publications:

Contact:

  • jolespin @ newatlantis . io

Aside from research:

Pinned Loading

  1. veba veba Public

    A modular end-to-end suite for in silico recovery, clustering, and analysis of prokaryotic, microeukaryotic, and viral genomes from metagenomes

    Python 79 9

  2. clairvoyance clairvoyance Public

    AutoML simultaneous bayesian hyperparameter optimization and feature selection

    Python 7

  3. pykofamsearch pykofamsearch Public

    Fast implementation of KofamScan optimized for high-memory systems using PyHmmer

    Python 11 1

  4. kegg_pathway_profiler kegg_pathway_profiler Public

    A pathway profiling tool designed for traversing metabolic pathway graphs, identifying most complete paths based on an evaluation set of KEGG orthologs (KO), and generalized for internal usage with…

    Python 2

  5. ensemble_networkx ensemble_networkx Public

    Python package for association, differential, clustered, and sample-specific ensemble networks. Direct support for compositional data analysis. Additional capabilities for feature engineering.

    Python 4 1

  6. compositional compositional Public

    Python package for compositional data analysis including CLR/ILR, proportionality, partial correlation with basis shrinkage, and visualizations.

    Python 17 1