AIMC Topic: Computational Biology

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Interpretable feature extraction and dimensionality reduction in ESM2 for protein localization prediction.

Briefings in bioinformatics
As the application of large language models (LLMs) has broadened into the realm of biological predictions, leveraging their capacity for self-supervised learning to create feature representations of amino acid sequences, these models have set a new b...

Enabling the clinical application of artificial intelligence in genomics: a perspective of the AMIA Genomics and Translational Bioinformatics Workgroup.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Given the importance AI in genomics and its potential impact on human health, the American Medical Informatics Association-Genomics and Translational Biomedical Informatics (GenTBI) Workgroup developed this assessment of factors that can f...

MEG-PPIS: a fast protein-protein interaction site prediction method based on multi-scale graph information and equivariant graph neural network.

Bioinformatics (Oxford, England)
MOTIVATION: Protein-protein interaction sites (PPIS) are crucial for deciphering protein action mechanisms and related medical research, which is the key issue in protein action research. Recent studies have shown that graph neural networks have achi...

scGraph2Vec: a deep generative model for gene embedding augmented by graph neural network and single-cell omics data.

GigaScience
BACKGROUND: Exploring the cellular processes of genes from the aspects of biological networks is of great interest to understanding the properties of complex diseases and biological systems. Biological networks, such as protein-protein interaction ne...

Protein-protein and protein-nucleic acid binding site prediction via interpretable hierarchical geometric deep learning.

GigaScience
Identification of protein-protein and protein-nucleic acid binding sites provides insights into biological processes related to protein functions and technical guidance for disease diagnosis and drug design. However, accurate predictions by computati...

CoCoPyE: feature engineering for learning and prediction of genome quality indices.

GigaScience
BACKGROUND: The exploration of the microbial world has been greatly advanced by the reconstruction of genomes from metagenomic sequence data. However, the rapidly increasing number of metagenome-assembled genomes has also resulted in a wide variation...

Deepdefense: annotation of immune systems in prokaryotes using deep learning.

GigaScience
BACKGROUND: Due to a constant evolutionary arms race, archaea and bacteria have evolved an abundance and diversity of immune responses to protect themselves against phages. Since the discovery and application of CRISPR-Cas adaptive immune systems, nu...

RNAVirHost: a machine learning-based method for predicting hosts of RNA viruses through viral genomes.

GigaScience
BACKGROUND: The high-throughput sequencing technologies have revolutionized the identification of novel RNA viruses. Given that viruses are infectious agents, identifying hosts of these new viruses carries significant implications for public health a...

spatiAlign: an unsupervised contrastive learning model for data integration of spatially resolved transcriptomics.

GigaScience
BACKGROUND: Integrative analysis of spatially resolved transcriptomics datasets empowers a deeper understanding of complex biological systems. However, integrating multiple tissue sections presents challenges for batch effect removal, particularly wh...

CheRRI-Accurate classification of the biological relevance of putative RNA-RNA interaction sites.

GigaScience
BACKGROUND: RNA-RNA interactions are key to a wide range of cellular functions. The detection of potential interactions helps to understand the underlying processes. However, potential interactions identified via in silico or experimental high-throug...