Our new editorial on equity, diversity, and inclusion in data science is out in BioData Mining ..read more

Romano JD, Moore JH. Ten simple rules for writing a paper about scientific software. PLoS Comput Biol. 2020 Nov 12;16(11):e1008390. doi: 10.1371/journal.pcbi.1008390. PMID: 33180774; PMCID: PMC7660560. [PubMed] [PLoS Comp Bio] Abstract Papers describing software are an important part of computational fields of scientific research. These "software papers" are unique in a number of ways, and they require special consideration to improve their impact on the scientific community and their efficacy at conveying important information. Here, we discuss 10 specific rules for writing software papers ..read more

Manduchi E, Fu W, Romano JD, Ruberto S, Moore JH. Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses. BMC Bioinformatics. 2020 Oct 1;21(1):430. doi: 10.1186/s12859-020-03755-4. PMID: 32998684; PMCID: PMC7528347. [PubMed] [BMC Bioinformatics] Abstract Background: A typical task in bioinformatics consists of identifying which features are associated with a target outcome of interest and building a predictive model. Automated machine learning (AutoML) systems such as the Tree-based Pipeline Optimization Tool (TPOT) constitute an appealing a ..read more

Moore JH. Ten important roles for academic leaders in data science. BioData Min. 2020 Oct 26;13:18. doi: 10.1186/s13040-020-00228-5. PMID: 33117434; PMCID: PMC7586691. [PubMed] [BioData Mining] Abstract Data science has emerged as an important discipline in the era of big data and biological and biomedical data mining. As such, we have seen a rapid increase in the number of data science departments, research centers, and schools. We review here ten important leadership roles for a successful academic data science chair, director, or dean. These roles include the visionary, executive, cheerlead ..read more

La Cava W, Williams H, Fu W, Vitale S, Srivatsan D, Moore JH. Evaluating recommender systems for AI-driven biomedical informatics. Bioinformatics. 2020 Aug 7:btaa698. doi: 10.1093/bioinformatics/btaa698. Epub ahead of print. PMID: 32766825. [PubMed] [Bioinformatics] Abstract Motivation: Many researchers with domain expertise are unable to easily apply machine learning to their bioinformatics data due to a lack of machine learning and/or coding expertise. Methods that have been proposed thus far to automate machine learning mostly require programming experience as well as expert knowledge to ..read more

Li R, Chen Y, Ritchie MD, Moore JH. Electronic health records and polygenic risk scores for predicting disease risk. Nat Rev Genet. 2020 Aug;21(8):493-502. doi: 10.1038/s41576-020-0224-1. Epub 2020 Mar 31. PMID: 32235907. [PubMed] [Nature Reviews] Abstract Accurate prediction of disease risk based on the genetic make-up of an individual is essential for effective prevention and personalized treatment. Nevertheless, to date, individual genetic variants from genome-wide association studies have achieved only moderate prediction of disease risk. The aggregation of genetic variants under a polygen ..read more

 A 12-minute overview of my artificial intelligence and machine learning research program [YouTube ..read more

Le TT, Moore JH. treeheatr: an R package for interpretable decision tree visualizations. Bioinformatics. 2020 Jul 23:btaa662. doi: 10.1093/bioinformatics/btaa662. Epub ahead of print. PMID: 32702108. [PubMed] [Bioinformatics] Abstract Summary: treeheatr is an R package for creating interpretable decision tree visualizations with the data represented as a heatmap at the tree's leaf nodes. The integrated presentation of the tree structure along with an overview of the data efficiently illustrates how the tree nodes split up the feature space and how well the tree model performs. This visual ..read more

Moore JH, Barnett I, Boland MR, Chen Y, Demiris G, Gonzalez-Hernandez G, Herman DS, Himes BE, Hubbard RA, Kim D, Morris JS, Mowery DL, Ritchie MD, Shen L, Urbanowicz R, Holmes JH. Ideas for how informaticians can get involved with COVID-19 research. BioData Min. 2020 May 12;13:3. doi: 10.1186/s13040-020-00213-y. PMID: 32419848; PMCID: PMC7216865. [PubMed] [BioData Mining] Abstract The coronavirus disease 2019 (COVID-19) pandemic has had a significant impact on population health and wellbeing. Biomedical informatics is central to COVID-19 research efforts and for the delivery of healthcare fo ..read more

Moore JH, Olson RS, Schmitt P, Chen Y, Manduchi E. How Computational Experiments Can Improve Our Understanding of the Genetic Architecture of Common Human Diseases. Artif Life. 2020 Winter;26(1):23-37. doi: 10.1162/artl_a_00308. Epub 2020 Feb 6. PMID: 32027528. [PubMed] [Artificial Life] Abstract Susceptibility to common human diseases such as cancer is influenced by many genetic and environmental factors that work together in a complex manner. The state of the art is to perform a genome-wide association study (GWAS) that measures millions of single-nucleotide polymorphisms (SNPs) throughout ..read more