2024-01-23 ラトガース大学
◆従来の統計手法と最先端の機械学習アルゴリズムを組み合わせ、個別の患者予測とバイオマーカーの視覚的表現を生成。別の研究では、IntelliGenesを使用して心血管疾患を高精度で予測。このソフトウェアは一般的および希少な疾患の個別早期検出をサポートし、新たな研究と治療法の可能性を開くとされている。
<関連情報>
- https://www.rutgers.edu/news/rutgers-health-researchers-develop-software-predict-diseases
- https://academic.oup.com/bioinformatics/article/39/12/btad755/7473370?login=false
IntelliGenes:マルチゲノムプロファイルを用いたバイオマーカー発見と予測分析のための新しい機械学習パイプライン IntelliGenes: a novel machine learning pipeline for biomarker discovery and predictive analysis using multi-genomic profiles
William DeGroat, Dinesh Mendhe, Atharva Bhusari, Habiba Abdelhalim, Saman Zeeshan, Zeeshan Ahmed
Bioinformatics Published:14 December 2023
DOI:https://doi.org/10.1093/bioinformatics/btad755
Abstract
Summary
In this article, we present IntelliGenes, a novel machine learning (ML) pipeline for the multi-genomics exploration to discover biomarkers significant in disease prediction with high accuracy. IntelliGenes is based on a novel approach, which consists of nexus of conventional statistical techniques and cutting-edge ML algorithms using multi-genomic, clinical, and demographic data. IntelliGenes introduces a new metric, i.e. Intelligent Gene (I-Gene) score to measure the importance of individual biomarkers for prediction of complex traits. I-Gene scores can be utilized to generate I-Gene profiles of individuals to comprehend the intricacies of ML used in disease prediction. IntelliGenes is user-friendly, portable, and a cross-platform application, compatible with Microsoft Windows, macOS, and UNIX operating systems. IntelliGenes not only holds the potential for personalized early detection of common and rare diseases in individuals, but also opens avenues for broader research using novel ML methodologies, ultimately leading to personalized interventions and novel treatment targets.
Availability and implementation
The source code of IntelliGenes is available on GitHub (https://github.com/drzeeshanahmed/intelligenes) and Code Ocean (https://codeocean.com/capsule/8638596/tree/v1).
