AIMC Topic: Computational Biology

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Improving prediction of bacterial sRNA regulatory targets with expression data.

NAR genomics and bioinformatics
Small regulatory RNAs (sRNAs) are widespread in bacteria. However, characterizing the targets of sRNA regulation in a way that scales with the increasing number of identified sRNAs has proven challenging. Computational methods offer one means for eff...

Deciphering the mechanism of baicalein in cervical cancer via bioinformatics, machine learning and computational simulations: PIM1 and CDK2 are key target proteins.

International journal of biological macromolecules
Cervical cancer is one of the leading causes of death among women worldwide. Current treatments are limited by chemoresistance and chemotherapeutic agents' adverse effects, prompting the search for better therapeutic alternatives. Baicalein, a natura...

AutoFE-Pointer: Auto-weighted feature extractor based on pointer network for DNA methylation prediction.

International journal of biological macromolecules
DNA methylation is a critical epigenetic modification that plays a central role in gene regulation, cellular differentiation, and the development of various diseases, including cancers. Aberrant methylation patterns have emerged as both biomarkers an...

IR-MBiTCN: Computational prediction of insulin receptor using deep learning: A multi-information fusion approach with multiscale bidirectional temporal convolutional network.

International journal of biological macromolecules
The insulin receptor (IR) is a transmembrane protein that controls glucose homeostasis and is highly associated with chronic diseases including cancer and neurological. Traditional experimental methods have provided essential insights into IR structu...

PregAN-NET: Addressing Class Imbalance with GANs in Interpretable Computational Framework for Predicting Safety Profile of Drugs Considering Adverse Reactions During Pregnancy.

Journal of biomedical informatics
Adverse Drug Reactions (ADRs) during pregnancy pose significant risks to both the mother and the fetus. Conventional approaches to predict ADR are inadequate due to ethical restrictions that prevent performing medication studies in pregnant women, le...

GBDTSVM: Combined Support Vector Machine and Gradient Boosting Decision Tree Framework for efficient snoRNA-disease association prediction.

Computers in biology and medicine
Small nucleolar RNAs (snoRNAs) are increasingly recognized for their critical role in the pathogenesis and characterization of various human diseases. Consequently, the precise identification of snoRNA-disease associations (SDAs) is essential for the...

Exploring pesticide risk in autism via integrative machine learning and network toxicology.

Ecotoxicology and environmental safety
Autism Spectrum Disorder (ASD) is a prevalent neurodevelopmental condition influenced by both genetic and environmental factors, including pesticide exposure. This study aims to investigate the pathogenic mechanisms of ASD and identify potential caus...

GDReCo: Fine-grained gene-disease relationship extraction corpus.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Understanding gene-disease relationships is crucial for medical research, drug discovery, clinical diagnosis, and other fields. However, there is currently no high-quality, fine-grained corpus available for training Natural ...

GOReverseLookup: A gene ontology reverse lookup tool.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: The Gene Ontology (GO) project has been pivotal in providing a structured framework for characterizing genes and annotating them to specific biological concepts. While traditional gene annotation primarily focuses on mapping...

Predicting host-pathogen interactions with machine learning algorithms: A scoping review.

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases
BACKGROUND: Diseases caused by pathogenic microorganisms pose a persistent global health challenge. Pathogens exploit host mechanisms through intricate molecular interactions. Understanding these host-pathogen interactions (HPIs), particularly protei...