Extreme Gradient Boosting Tuned with Metaheuristic Algorithms for Predicting Myeloid NGS Onco-Somatic Variant Pathogenicity

Extreme Gradient Boosting Tuned with Metaheuristic Algorithms for Predicting Myeloid NGS Onco-Somatic Variant Pathogenicity

The advent of next-generation sequencing (NGS) technologies has revolutionized the field of bioinformatics and genomics, particularly in the area of onco-somatic genetics. NGS has provided a wealth of information about the genetic changes that underlie cancer and has considerably improved our abilit...

Cijeli opis

Bibliografski detalji
Glavni autori: Eric Pellegrino, Clara Camilla, Norman Abbou, Nathalie Beaufils, Christel Pissier, Jean Gabert, Isabelle Nanni-Metellus, L’Houcine Ouafik
Format: Članak
Jezik:English
Izdano: MDPI AG 2023-06-01
Serija:Bioengineering
Teme:
extreme gradient boosting (XGBoost)
metaheuristic algorithms
onco-somatic
next-generation sequencing
bioinformatics
myeloid
Online pristup:https://www.mdpi.com/2306-5354/10/7/753

Internet

https://www.mdpi.com/2306-5354/10/7/753

Slični predmeti