Gustavo Arango-Argoty

An artificial intelligence-based model for prediction of Clonal Hematopoiesis mutants in cell-free DNA samples

The paper presents a machine learning framework to classify variants in cell-free DNA as clonal hematopoiesis or tumor origin, achieving better classification rates than existing methods.

Integrating Knowledge Graphs into Machine Learning Models for Survival Prediction and Biomarker Discovery in Patients with Non-Small-Cell Lung Cancer

The paper integrates knowledge graphs into machine learning models to improve survival prediction and biomarker discovery in non-small-cell lung cancer patients, showing significant improvements in hazard ratios and overall survival differentiation.

MetaMLP: A fast word embedding based classifier to profile target gene databases in metagenomic samples

MetaMLP is a machine learning classifier for metagenomic functional profiling that uses word embeddings and a neural network to achieve high accuracy and speed.

ARG-miner: A web platform for crowdsourcing-based curation of antibiotic resistance genes

ARG-miner is a crowdsourcing-based platform for curating antibiotic resistance genes, achieving high accuracy and efficiency compared to manual curation.

NanoARG: A web service for identification of antimicrobial resistance elements from nanopore-derived environmental metagenomes

NanoARG identifies antimicrobial resistance elements from nanopore-derived environmental metagenomes, enabling analysis of ARGs, MRGs, MGEs, and pathogens.

DeepARG: A deep learning approach for predicting antibiotic resistance genes from metagenomic data

This paper introduces deepARG, a deep learning method for predicting antibiotic resistance genes from metagenomic data, achieving high precision and recall over traditional methods.