Alejandro Lopez‐Rincon

This paper uses AI to develop a primer set for the SARS-CoV-2 Omicron variant, validated in silico and preliminarily in lab tests.

The paper designs specific primer sets for SARS-CoV-2 variants using AI, showing high accuracy and potential for multiplexed testing.

The paper designs a specific primer set for detecting the B.1.1.7 SARS-CoV-2 variant using deep learning, achieving >99% accuracy with in-silico validation.

The paper proposes a feature selection method to identify key miRNAs for cancer classification, finds a signature of 100 miRNAs that accurately classify 29 cancer types, and discovers 15 new potential biomarkers through literature meta-analysis.