AIMC Topic: Machine Learning

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Decoding brand sentiments: Leveraging customer reviews for insightful brand perception analysis using natural language processing and Tableau.

PloS one
Traditional survey-based feedback has given way to real-time online reviews, yet transforming this unstructured text into actionable knowledge remains difficult. Focusing on the highly competitive smartphone market, where customer sentiment shapes br...

Temporal shifts in prognostic factors for 90- and 180-day outcomes after stroke thrombolysis: A machine learning analysis.

PloS one
INTRODUCTION: Prognostication at 90 and 180 days after thrombolysis for acute ischemic stroke (AIS) is critical, yet the temporal evolution of key predictors remains inadequately understood. The utility of machine learning for systematically comparin...

ProSECFPs: A Novel Fingerprint-Based Protein Representation Method for Missense Mutation Pathogenicity Prediction.

Journal of chemical information and modeling
Developing effective computational representations of protein sequences is crucial for advancing diverse areas of computational biology and bioinformatics. Ideal representations must be computationally efficient, scalable, informative, flexible acros...

ThermoPred: AI-Enhanced Quantum Chemistry Data Set and ML Toolkit for Thermochemical Properties of API-Like Compounds and Their Degradants.

Journal of chemical information and modeling
In this work, we present an open-access quantum-chemistry database of more than 14,500 API-like molecules and their degradation products, all optimized at the M06-2/6-31G(d) compound model. The data set delivers a comprehensive suite of thermochemica...

Machine learning enables de novo multiepitope design of circumsporozoite protein to target trimeric L9 antibody.

Proceedings of the National Academy of Sciences of the United States of America
Currently approved vaccines for the prevention of malaria provide only partial protection against disease due to high variability in the quality of induced antibodies. These vaccines present the unstructured central repeat region, as well as the C-te...

Maternal lipidomic signatures of preterm and small-for-gestational-age newborn infants in low- and middle-income countries.

Science advances
Maternal lipid levels change dynamically during gestation to support normal fetal growth. To obtain a detailed footprint of these changes and their differences in pregnancies with preterm or small-for-gestational-age (SGA) neonates, we analyzed 641 l...

Proteome-wide computational analyses reveal links between protein condensate formation and RNA biology.

Science advances
Biomolecular condensates mediate dynamic compartmentalization of cellular processes. The multivalent interactions that underlie biomolecular condensation are often promoted by intrinsically disordered regions (IDRs) within proteins. Although the role...

Enhancing kinase-inhibitor activity and selectivity prediction through contrastive learning.

Nature communications
Developing selective kinase inhibitors is challenging due to the conserved kinase structures and costly kinome profiling experiments, highlighting the need for accurate prediction of kinase-inhibitor affinity and specificity. Here we present MMCLKin,...

Advances in surrogate modeling for biological agent-based simulations: trends, challenges, and future prospects.

Journal of mathematical biology
Agent-based modeling (ABM) is a powerful computational approach for studying complex biological and biomedical systems, yet its widespread use remains limited by significant computational demands. As models become increasingly sophisticated, the numb...

ML-MAGES enables multivariate genetic association analyses with genes and effect size shrinkage.

Genome research
A fundamental goal of genetics is to identify which and how genetic variants are associated with a trait, often using the regression results from genome-wide association (GWA) studies. Important methodological challenges account for inflation in GWA ...