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Emmanuel Martínez 0001

dblp:67/2772 · also Emmanuel Martínez-Ledesma · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0000-0003-1191-7917ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
genomics
0.912025
FuNTB: a functional network clustering tool for the analysis of genome-wide genetic variants in Mycobacterium tuberculosis · Bioinform. 2025
Bioinformatics and computational biology › genomics
variant analysis
0.912025
FuNTB: a functional network clustering tool for the analysis of genome-wide genetic variants in Mycobacterium tuberculosis · Bioinform. 2025
Bioinformatics and computational biology › genomics
pathogen genomics
0.312025
FuNTB: a functional network clustering tool for the analysis of genome-wide genetic variants in Mycobacterium tuberculosis · Bioinform. 2025

Methods — techniques the papers use, named apart from their topics

network clustering · 0.9SNP detection · 0.9
YearPublicationVenuePosition
2025 FuNTB: a functional network clustering tool for the analysis of genome-wide genetic variants in Mycobacterium tuberculosis
abstract
MOTIVATION: Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), still claims around 1.25 million lives each year. The growing threat of drug resistance-often driven by single‑nucleotide polymorphisms (SNPs) in Mtb genomes underscores the need for high‑quality genomic data and powerful bioinformatics tools. We present FuNTB, a python‑based pipeline that detects non‑synonymous SNPs in Mtb and builds functional network clusters to reveal genotype-phenotype relationships. RESULTS: FuNTB profiles non‑synonymous SNPs at the gene level across user‑defined phenotypes, pinpointing both shared and unique mutations. It ingests annotated Variant Call Format (VCF) files or MTBseq outputs and merges them with clinical metadata to produce network‑XML files compatible with Cytoscape and Gephi. When applied to the CRyPTIC Mtb collection, FuNTB rapidly recovered established resistance genes and surfaced novel candidates, validating its utility for mapping genotype-phenotype associations. AVAILABILITY AND IMPLEMENTATION: FuNTB is implemented in Python 3.8+ and is freely available under the MIT license at https://doi.org/10.5281/zenodo.15399917.
Axel Alejandro Ramos García, Paulina M. Mejía-Ponce, Nelly Sélem-Mojica, Alejandro Santos-Díaz, Emmanuel Martínez 0001, Cuauhtémoc Licona Cassani
Bioinform.5