David Guevara-Barrientos

ORCID: 0000-0003-3117-0777
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About
Contact & Profiles
Research Areas
  • Genomics and Phylogenetic Studies
  • Chromosomal and Genetic Variations
  • Machine Learning in Bioinformatics
  • Protein Structure and Dynamics
  • Algorithms and Data Compression
  • Plant Virus Research Studies
  • vaccines and immunoinformatics approaches
  • Bioinformatics and Genomic Networks

Utah State University
2022-2024

Universidad de Los Andes
2023

Universidad de Los Andes
2022

10.1016/j.csbj.2022.12.044 article EN cc-by-nc-nd Computational and Structural Biotechnology Journal 2022-12-29

Building de novo genome assemblies for complex genomes is possible thanks to long-read DNA sequencing technologies. However, maximizing the quality of based on long reads a challenging task that requires development specialized data analysis techniques. We present new algorithms assembling from haploid and diploid organisms. The assembly algorithm builds an undirected graph with two vertices each read minimizers selected by hash function derived k-mer distribution. Statistics collected...

10.26508/lsa.202201719 article EN cc-by Life Science Alliance 2023-02-22

COVID 19 pandemic is still ongoing, having taken more than 6 million human lives with it, and it seems that the world will have to learn how live virus around. In consequence, there a need develop different treatments against not only vaccines, but also new medicines. To do this, human-virus protein-protein interactions (PPIs) play key part in drug-target discovery, finding them experimentally can be either costly or sometimes unreliable. Therefore, computational methods arose as powerful...

10.1177/11779322241263671 article EN cc-by-nc Bioinformatics and Biology Insights 2024-01-01

Abstract Producing de-novo genome assemblies for complex genomes is possible thanks to long-read DNA sequencing technologies. However, maximizing the quality of based on long reads a challenging task that requires development specialized data analysis techniques. In this paper, we present new algorithms assembling long-DNA from haploid and diploid organisms. The assembly algorithm builds an undirected graph with two vertices each read minimizers selected by hash function derived k-mers...

10.1101/2022.08.30.505891 preprint EN cc-by bioRxiv (Cold Spring Harbor Laboratory) 2022-09-01
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