AIMC Topic: Computational Biology

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CFINet: Cross-Modality MRI Feature Interaction Network for Pseudoprogression Prediction of Glioblastoma.

Journal of computational biology : a journal of computational molecular cell biology Jul 8, 2024
Pseudoprogression (PSP) is a related reaction of glioblastoma treatment, and misdiagnosis can lead to unnecessary intervention. Magnetic resonance imaging (MRI) provides cross-modality images for PSP prediction studies. However, how to effectively us...
Neural Networks, Computer Algorithms Brain Neoplasms Disease Progression Computational Biology Magnetic Resonance Imaging Glioblastoma Humans
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PreDBP-PLMs: Prediction of DNA-binding proteins based on pre-trained protein language models and convolutional neural networks.

Analytical biochemistry Jul 8, 2024
The recognition of DNA-binding proteins (DBPs) is the crucial step to understanding their roles in various biological processes such as genetic regulation, gene expression, cell cycle control, DNA repair, and replication within cells. However, conven...
Databases, Protein DNA-Binding Proteins Neural Networks, Computer Computational Biology Humans
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Ensemble Machine Learning and Predicted Properties Promote Antimicrobial Peptide Identification.

Interdisciplinary sciences, computational life sciences Jul 7, 2024
The emergence of antibiotic-resistant microbes raises a pressing demand for novel alternative treatments. One promising alternative is the antimicrobial peptides (AMPs), a class of innate immunity mediators within the therapeutic peptide realm. AMPs ...
Antimicrobial Peptides Algorithms Neural Networks, Computer Deep Learning Computational Biology Machine Learning
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Identification and validation of potential common biomarkers for papillary thyroid carcinoma and Hashimoto's thyroiditis through bioinformatics analysis and machine learning.

Scientific reports Jul 6, 2024
There is a growing body of evidence suggesting that Hashimoto's thyroiditis (HT) may contribute to an increased risk of papillary thyroid carcinoma (PTC). However, the exact relationship between HT and PTC is still not fully understood. The objective...
Hashimoto Disease Thyroid Cancer, Papillary Gene Regulatory Networks Computational Biology Gene Expression Regulation, Neoplastic Thyroid Neoplasms Protein Interaction Maps Humans Neural Networks, Computer Machine Learning Biomarkers, Tumor Gene Expression Profiling
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Screening of Secretory Proteins Linking Major Depressive Disorder with Heart Failure Based on Comprehensive Bioinformatics Analysis and Machine Learning.

Biomolecules Jul 4, 2024
BACKGROUND: Major depressive disorder (MDD) plays a crucial role in the occurrence of heart failure (HF). This investigation was undertaken to explore the possible mechanism of MDD's involvement in HF pathogenesis and identify candidate biomarkers fo...
Animals Depressive Disorder, Major Genome-Wide Association Study Humans Machine Learning Biomarkers Mendelian Randomization Analysis Heart Failure Protein Interaction Maps Mice Computational Biology
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Characterizing mitochondrial features in osteoarthritis through integrative multi-omics and machine learning analysis.

Frontiers in immunology Jul 4, 2024
PURPOSE: Osteoarthritis (OA) stands as the most prevalent joint disorder. Mitochondrial dysfunction has been linked to the pathogenesis of OA. The main goal of this study is to uncover the pivotal role of mitochondria in the mechanisms driving OA dev...
Gene Regulatory Networks Gene Expression Profiling Humans Computational Biology Transcriptome Multiomics Databases, Genetic Machine Learning Genome-Wide Association Study Mitochondria Osteoarthritis
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A variational autoencoder trained with priors from canonical pathways increases the interpretability of transcriptome data.

PLoS computational biology Jul 3, 2024
Interpreting transcriptome data is an important yet challenging aspect of bioinformatic analysis. While gene set enrichment analysis is a standard tool for interpreting regulatory changes, we utilize deep learning techniques, specifically autoencoder...
Gene Expression Profiling Transcriptome Deep Learning Humans Algorithms Computational Biology
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Comprehensive Bioinformatics Analysis and Machine Learning of TTK as a Transhepatic Arterial Chemoembolization Resistance Target in Hepatocellular Carcinoma.

Molecular biotechnology Jul 2, 2024
Transhepatic arterial chemoembolization (TACE) is the standard treatment for intermediate-stage hepatocellular carcinoma (HCC). However, a significant proportion of patients are non-responders or poor responders to TACE. Therefore, our aim is to iden...
Carcinoma, Hepatocellular Protein Interaction Maps Computational Biology Biomarkers, Tumor Humans Gene Expression Profiling Chemoembolization, Therapeutic Gene Expression Regulation, Neoplastic Liver Neoplasms Machine Learning Kaplan-Meier Estimate Databases, Genetic Prognosis Cell Cycle Proteins Drug Resistance, Neoplasm
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Machine-learning-based structural analysis of interactions between antibodies and antigens.

Bio Systems Jul 2, 2024
Computational analysis of paratope-epitope interactions between antibodies and their corresponding antigens can facilitate our understanding of the molecular mechanism underlying humoral immunity and boost the design of new therapeutics for many dise...
Antigens Binding Sites Antigen-Antibody Complex Computational Biology Antibodies Epitopes Binding Sites, Antibody Humans Machine Learning Deep Learning Protein Binding
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Accurate Prediction of Protein Structural Flexibility by Deep Learning Integrating Intricate Atomic Structures and Cryo-EM Density Information.

Nature communications Jul 2, 2024
The dynamics of proteins are crucial for understanding their mechanisms. However, computationally predicting protein dynamic information has proven challenging. Here, we propose a neural network model, RMSF-net, which outperforms previous methods and...
Molecular Dynamics Simulation Computational Biology Protein Conformation Proteins Cryoelectron Microscopy Databases, Protein Neural Networks, Computer Deep Learning
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