AIMC Topic: Computational Biology
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PLMACPred prediction of anticancer peptides based on protein language model and wavelet denoising transformation.
Scientific reports
Jul 23, 2024
Anticancer peptides (ACPs) perform a promising role in discovering anti-cancer drugs. The growing research on ACPs as therapeutic agent is increasing due to its minimal side effects. However, identifying novel ACPs using wet-lab experiments are gener...
Computational approaches for clinical, genomic and proteomic markers of response to glucagon-like peptide-1 therapy in type-2 diabetes mellitus: An exploratory analysis with machine learning algorithms.
Diabetes & metabolic syndrome
Jul 23, 2024
INTRODUCTION: In 2021, the International Diabetes Federation reported that 537 million people worldwide are living with diabetes. While glucagon-like peptide-1 agonists provide significant benefits in diabetes management, approximately 40% of patient...
Machine learning and bioinformatics analysis of diagnostic biomarkers associated with the occurrence and development of lung adenocarcinoma.
PeerJ
Jul 23, 2024
OBJECTIVE: Lung adenocarcinoma poses a major global health challenge and is a leading cause of cancer-related deaths worldwide. This study is a review of three molecular biomarkers screened by machine learning that are not only important in the occur...
Contextual AI models for single-cell protein biology.
Nature methods
Jul 22, 2024
Understanding protein function and developing molecular therapies require deciphering the cell types in which proteins act as well as the interactions between proteins. However, modeling protein interactions across biological contexts remains challen...
Computational Insights into Reproductive Toxicity: Clustering, Mechanism Analysis, and Predictive Models.
International journal of molecular sciences
Jul 22, 2024
Reproductive toxicity poses significant risks to fertility and progeny health, making its identification in pharmaceutical compounds crucial. In this study, we conducted a comprehensive in silico investigation of reproductive toxic molecules, identif...
Quantifying massively parallel microbial growth with spatially mediated interactions.
PLoS computational biology
Jul 22, 2024
Quantitative understanding of microbial growth is an essential prerequisite for successful control of pathogens as well as various biotechnology applications. Even though the growth of cell populations has been extensively studied, microbial growth r...
TabDEG: Classifying differentially expressed genes from RNA-seq data based on feature extraction and deep learning framework.
PloS one
Jul 22, 2024
Traditional differential expression genes (DEGs) identification models have limitations in small sample size datasets because they require meeting distribution assumptions, otherwise resulting high false positive/negative rates due to sample variatio...
PMTPred: machine-learning-based prediction of protein methyltransferases using the composition of k-spaced amino acid pairs.
Molecular diversity
Jul 21, 2024
Protein methyltransferases (PMTs) are a group of enzymes that help catalyze the transfer of a methyl group to its substrates. These enzymes play an important role in epigenetic regulation and can methylate various substrates with DNA, RNA, protein, a...
Abnormal genes and pathways that drive muscle contracture from brachial plexus injuries: Towards machine learning approach.
SLAS technology
Jul 20, 2024
In order to clarify the pathways closely linked to denervated muscle contracture, this work uses IoMT-enabled healthcare stratergies to examine changes in gene expression patterns inside atrophic muscles following brachial plexus damage. The gene exp...
Gtie-Rt: A comprehensive graph learning model for predicting drugs targeting metabolic pathways in human.
Journal of bioinformatics and computational biology
Jul 20, 2024
Drugs often target specific metabolic pathways to produce a therapeutic effect. However, these pathways are complex and interconnected, making it challenging to predict a drug's potential effects on an organism's overall metabolism. The mapping of dr...
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