AIMC Topic: Software

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XGBoost based machine learning approach to predict the risk of fall in older adults using gait outcomes.

Scientific reports
This study aimed to identify the optimal features of gait parameters to predict the fall risk level in older adults. The study included 746 older adults (age: 63-89 years). Gait tests (20 m walkway) included speed modification (slower, preferred, and...

DNAscent v2: detecting replication forks in nanopore sequencing data with deep learning.

BMC genomics
BACKGROUND: Measuring DNA replication dynamics with high throughput and single-molecule resolution is critical for understanding both the basic biology behind how cells replicate their DNA and how DNA replication can be used as a therapeutic target f...

MLatom 2: An Integrative Platform for Atomistic Machine Learning.

Topics in current chemistry (Cham)
Atomistic machine learning (AML) simulations are used in chemistry at an ever-increasing pace. A large number of AML models has been developed, but their implementations are scattered among different packages, each with its own conventions for input ...

Robust diagnostic classification via Q-learning.

Scientific reports
Machine learning (ML) models have demonstrated the power of utilizing clinical instruments to provide tools for domain experts in gaining additional insights toward complex clinical diagnoses. In this context these tools desire two additional propert...

AlphaFold - A Personal Perspective on the Impact of Machine Learning.

Journal of molecular biology
I outline how over my career as a protein scientist Machine Learning has impacted my area of science and one of my pastimes, chess, where there are some interesting parallels. In 1968, modelling of three-dimensional structures was initiated based on ...

Recent Applications of Deep Learning Methods on Evolution- and Contact-Based Protein Structure Prediction.

International journal of molecular sciences
The new advances in deep learning methods have influenced many aspects of scientific research, including the study of the protein system. The prediction of proteins' 3D structural components is now heavily dependent on machine learning techniques tha...

Learning from crowds in digital pathology using scalable variational Gaussian processes.

Scientific reports
The volume of labeled data is often the primary determinant of success in developing machine learning algorithms. This has increased interest in methods for leveraging crowds to scale data labeling efforts, and methods to learn from noisy crowd-sourc...

MetaVelvet-DL: a MetaVelvet deep learning extension for de novo metagenome assembly.

BMC bioinformatics
BACKGROUND: The increasing use of whole metagenome sequencing has spurred the need to improve de novo assemblers to facilitate the discovery of unknown species and the analysis of their genomic functions. MetaVelvet-SL is a short-read de novo metagen...

coupleCoC+: An information-theoretic co-clustering-based transfer learning framework for the integrative analysis of single-cell genomic data.

PLoS computational biology
Technological advances have enabled us to profile multiple molecular layers at unprecedented single-cell resolution and the available datasets from multiple samples or domains are growing. These datasets, including scRNA-seq data, scATAC-seq data and...

Utilizing Whole Slide Images for the Primary Evaluation and Peer Review of a GLP-Compliant Rodent Toxicology Study.

Toxicologic pathology
The approach undertaken to deliver a Good Laboratory Practice (GLP) validation of whole slide images (WSIs) and the associated workflow for the digital primary evaluation and peer review of a GLP-compliant rodent inhalation toxicity study is describe...