AIMC Topic: Computational Biology

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Intra-Inter Graph Representation Learning for Protein-Protein Binding Sites Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Graph neural networks have drawn increasing attention and achieved remarkable progress recently due to their potential applications for a large amount of irregular data. It is a natural way to represent protein as a graph. In this work, we focus on p...
Proteins Databases, Protein Ligands Protein Binding Computational Biology Machine Learning Neural Networks, Computer Binding Sites Algorithms
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SAGCN: Using Graph Convolutional Network With Subgraph-Aware for circRNA-Drug Sensitivity Identification.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Circular RNAs (circRNAs) play a significant role in cancer development and therapy resistance. There is substantial evidence indicating that the expression of circRNAs affects the sensitivity of cells to drugs. Identifying circRNAs-drug sensitivity a...
Neural Networks, Computer RNA, Circular Algorithms Neoplasms Humans Antineoplastic Agents Computational Biology
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Distantly Supervised Biomedical Relation Extraction via Negative Learning and Noisy Student Self-Training.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Biomedical relation extraction aims to identify underlying relationships among entities, such as gene associations and drug interactions, within biomedical texts. Despite advancements in relation extraction in general knowledge domains, the scarcity ...
Databases, Factual Computational Biology Data Mining Supervised Machine Learning Humans Algorithms
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Prediction of Inter-Residue Multiple Distances and Exploration of Protein Multiple Conformations by Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
AlphaFold2 has achieved a major breakthrough in end-to-end prediction for static protein structures. However, protein conformational change is considered to be a key factor in protein biological function. Inter-residue multiple distances prediction i...
Algorithms Protein Conformation Deep Learning Computational Biology Databases, Protein Models, Molecular Proteins
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Transcription Factor Binding Site Prediction Using CnNet Approach.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Controlling the gene expression is the most important development in a living organism, which makes it easier to find different kinds of diseases and their causes. It's very difficult to know what factors control the gene expression. Transcription Fa...
Sequence Analysis, DNA Humans Binding Sites Computational Biology Transcription Factors Algorithms Deep Learning Neural Networks, Computer
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RGCNPPIS: A Residual Graph Convolutional Network for Protein-Protein Interaction Site Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Accurate identification of protein-protein interaction (PPI) sites is crucial for understanding the mechanisms of biological processes, developing PPI networks, and detecting protein functions. Currently, most computational methods primarily concentr...
Protein Interaction Mapping Databases, Protein Binding Sites Neural Networks, Computer Algorithms Computational Biology Proteins Protein Interaction Maps Humans
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A Multi-Task Deep Feature Selection Method for Brain Imaging Genetics.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Using brain imaging quantitative traits (QTs) for identifying genetic risk factors is an important research topic in brain imaging genetics. Many efforts have been made for this task via building linear models between imaging QTs and genetic factors ...
Humans Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Polymorphism, Single Nucleotide Algorithms Brain Neuroimaging Computational Biology Linear Models
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ATP_mCNN: Predicting ATP binding sites through pretrained language models and multi-window neural networks.

Computers in biology and medicine Dec 8, 2024
Adenosine triphosphate plays a vital role in providing energy and enabling key cellular processes through interactions with binding proteins. The increasing amount of protein sequence data necessitates computational methods for identifying binding si...
Computational Biology Proteins Adenosine Triphosphate Binding Sites Databases, Protein Humans Neural Networks, Computer
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VaxOptiML: leveraging machine learning for accurate prediction of MHC-I and II epitopes for optimized cancer immunotherapy.

Immunogenetics Dec 7, 2024
Cancer immunotherapy hinges on accurate epitope prediction for advancing vaccine development. VaxOptiML (available at https://vaxoptiml.streamlit.app/ ) is an integrated pipeline designed to enhance epitope prediction and prioritization. This study a...
Software Neoplasms Epitopes, T-Lymphocyte Humans Cancer Vaccines Histocompatibility Antigens Class I Computational Biology Machine Learning Histocompatibility Antigens Class II Immunotherapy
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Simple and effective embedding model for single-cell biology built from ChatGPT.

Nature biomedical engineering Dec 6, 2024
Large-scale gene-expression data are being leveraged to pretrain models that implicitly learn gene and cellular functions. However, such models require extensive data curation and training. Here we explore a much simpler alternative: leveraging ChatG...
Computational Biology Generative Artificial Intelligence Gene Expression Profiling Single-Cell Analysis Humans Algorithms
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