AIMC Topic: Computational Biology
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TransBind allows precise detection of DNA-binding proteins and residues using language models and deep learning.
Communications biology
Apr 5, 2025
Identifying DNA-binding proteins and their binding residues is critical for understanding diverse biological processes, but conventional experimental approaches are slow and costly. Existing machine learning methods, while faster, often lack accuracy...
Grain protein function prediction based on improved FCN and bidirectional LSTM.
Food chemistry
Apr 4, 2025
With the development of high-throughput sequencing technologies, predicting grain protein function from amino acid sequences based on intelligent model has become one of the significant tasks in bioinformatics. The soybean, maize, indica, and japonic...
DeepAssembly2: A Web Server for Protein Complex Structure Assembly Based on Domain-Domain Interactions.
Journal of molecular biology
Apr 4, 2025
Proteins often perform biological functions by forming complexes, thereby accurately predicting the structure of protein complexes is crucial to understanding and mastering their functions, as well as facilitating drug discovery. Protein monomeric st...
Predicting genes associated with ossification of the posterior longitudinal ligament using graph attention network.
Methods (San Diego, Calif.)
Apr 4, 2025
Ossification of the posterior longitudinal ligament is a degenerative disease that severely impacts the spine, with a complex pathogenesis involving the interplay of multiple genes. This study utilizes a combination of graph neural networks and deep ...
RPI-GGCN: Prediction of RNA-Protein Interaction Based on Interpretability Gated Graph Convolution Neural Network and Co-Regularized Variational Autoencoders.
IEEE transactions on neural networks and learning systems
Apr 4, 2025
RNA-protein interactions (RPIs) play an important role in several fundamental cellular physiological processes, including cell motility, chromosome replication, transcription and translation, and signaling. Predicting RPI can guide the exploration of...
SeqNovo: De Novo Peptide Sequencing Prediction in IoMT via Seq2Seq.
IEEE journal of biomedical and health informatics
Apr 4, 2025
In the Internet of Medical Things (IoMT), de novo peptide sequencing prediction is one of the most important techniques for the fields of disease prediction, diagnosis, and treatment. Recently, deep-learning-based peptide sequencing prediction has be...
Self-Supervised Graph Representation Learning for Single-Cell Classification.
Interdisciplinary sciences, computational life sciences
Apr 3, 2025
Accurately identifying cell types in single-cell RNA sequencing data is critical for understanding cellular differentiation and pathological mechanisms in downstream analysis. As traditional biological approaches are laborious and time-intensive, it ...
Mitigating ambient RNA and doublets effects on single cell transcriptomics analysis in cancer research.
Cancer letters
Apr 3, 2025
In cancer biology, where understanding the tumor microenvironment at high resolution is vital, ambient RNA contamination becomes a considerable problem. This hinders accurate delineation of intratumoral heterogeneity, complicates the identification o...
Machine learning approaches enable the discovery of therapeutics across domains.
Molecular therapy : the journal of the American Society of Gene Therapy
Apr 3, 2025
Multi-modal datasets have grown exponentially in the last decade. This has created an enormous demand for machine learning models that can predict complex outcomes by leveraging cellular, molecular, and humoral profiles. Corresponding inference of me...
How did we get there? AI applications to biological networks and sequences.
Computers in biology and medicine
Apr 3, 2025
The rapidly advancing field of artificial intelligence (AI) has transformed numerous scientific domains, including biology, where a vast and complex volume of data is available for analysis. This paper provides a comprehensive overview of the current...
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