AIMC Topic: Computational Biology

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SCATrans: semantic cross-attention transformer for drug-drug interaction predication through multimodal biomedical data.

BMC bioinformatics
Predicting potential drug-drug interactions (DDIs) from biomedical data plays a critical role in drug therapy, drug development, drug regulation, and public health. However, it remains challenging due to the large number of possible drug combinations...

Fusing multisensory signals across channels and time.

PLoS computational biology
Animals continuously combine information across sensory modalities and time, and use these combined signals to guide their behaviour. Picture a predator watching their prey sprint and screech through a field. To date, a range of multisensory algorith...

The latest advances with natural products in drug discovery and opportunities for the future: a 2025 update.

Expert opinion on drug discovery
INTRODUCTION: The landscape of drug discovery is rapidly evolving, with natural products (NPs) playing a pivotal role in the development of novel therapeutics. Despite their historical significance, challenges persist in fully harnessing their potent...

MFDSMC: Accurate Identification of Cancer-Driver Synonymous Mutations Using Multiperspective Feature Representation Learning.

Journal of chemical information and modeling
Synonymous mutations do not change amino acid sequences, but they can drive cancer by influencing splicing, mRNA structure, translation efficiency, and other molecular mechanisms. Although driver synonymous mutations are significantly outnumbered by ...

Designing diverse and high-performance proteins with a large language model in the loop.

PLoS computational biology
We present a protein engineering approach to directed evolution with machine learning that integrates a new semi-supervised neural network fitness prediction model, Seq2Fitness, and an innovative optimization algorithm, biphasic annealing for diverse...

A descriptor-free machine learning framework to improve antigen discovery for bacterial pathogens.

PloS one
Identifying protective antigens (PAs), i.e., targets for bacterial vaccines, is challenging as conducting in-vivo tests at the proteome scale is impractical. Reverse Vaccinology (RV) aids in narrowing down the pool of candidates through computational...

GNNMutation: a heterogeneous graph-based framework for cancer detection.

BMC bioinformatics
BACKGROUND: When genes are translated into proteins, mutations in the gene sequence can lead to changes in protein structure and function as well as in the interactions between proteins. These changes can disrupt cell function and contribute to the d...

HLN-DDI: hierarchical molecular representation learning with co-attention mechanism for drug-drug interaction prediction.

BMC bioinformatics
BACKGROUND: Accurate identification of drug-drug interactions (DDIs) is critical in pharmacology, as DDIs can either enhance therapeutic efficacy or trigger adverse reactions when multiple medications are administered concurrently. Traditional method...

Efficient structure learning of gene regulatory networks with Bayesian active learning.

BMC bioinformatics
BACKGROUND: Gene regulatory network modeling is a complex structure learning problem that involves both observational data analysis and experimental interventions. Bayesian causal discovery provides a principled framework for modeling observational d...

Exploration of the potential therapeutic effects and targets of Coriandrum sativum on non-erosive esophagitis based on bioinformatics and molecular dynamics simulation.

Scientific reports
Gastroesophageal reflux disease (GERD) is one of the most frequently diagnosed gastrointestinal disorders, adversely affecting quality of life. Coriandrum sativum has been shown to effectively promote gastrointestinal motility, alleviate gastric disc...