AIMC Topic: Peptides

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ESM-BBB-Pred: a fine-tuned ESM 2.0 and deep neural networks for the identification of blood-brain barrier peptides.

Briefings in bioinformatics Nov 22, 2024
Blood-brain barrier peptides (BBBP) could significantly improve the delivery of drugs to the brain, paving the way for new treatments for central nervous system (CNS) disorders. The primary challenge in treating CNS disorders lies in the difficulty p...
Blood-Brain Barrier Peptides Humans Neural Networks, Computer Deep Learning Computational Biology
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Attention-aware differential learning for predicting peptide-MHC class I binding and T cell receptor recognition.

Briefings in bioinformatics Nov 22, 2024
The identification of neoantigens is crucial for advancing vaccines, diagnostics, and immunotherapies. Despite this importance, a fundamental question remains: how to model the presentation of neoantigens by major histocompatibility complex class I m...
Humans Machine Learning Algorithms Histocompatibility Antigens Class I Protein Binding Peptides Computational Biology Receptors, Antigen, T-Cell
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Toward molecular diagnosis of major depressive disorder by plasma peptides using a deep learning approach.

Briefings in bioinformatics Nov 22, 2024
Major depressive disorder (MDD) is a severe psychiatric disorder that currently lacks any objective diagnostic markers. Here, we develop a deep learning approach to discover the mass spectrometric features that can discriminate MDD patients from heal...
Depressive Disorder, Major Deep Learning Humans Biomarkers Peptides Neural Networks, Computer
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Leveraging Cancer Therapy Peptide Data: A Case Study on Machine Learning Application in Accelerating Cancer Research.

Studies in health technology and informatics Nov 22, 2024
This study leverages the DCTPep database, a comprehensive repository of cancer therapy peptides, to explore the application of machine learning in accelerating cancer research. We applied Principal Component Analysis (PCA) and K-means clustering to c...
Humans Machine Learning Antineoplastic Agents Databases, Protein Principal Component Analysis Neoplasms Peptides
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MultiFeatVotPIP: a voting-based ensemble learning framework for predicting proinflammatory peptides.

Briefings in bioinformatics Sep 23, 2024
Inflammatory responses may lead to tissue or organ damage, and proinflammatory peptides (PIPs) are signaling peptides that can induce such responses. Many diseases have been redefined as inflammatory diseases. To identify PIPs more efficiently, we ex...
Algorithms Peptides Voting Machine Learning Software Computational Biology Inflammation Humans
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AutoPeptideML: a study on how to build more trustworthy peptide bioactivity predictors.

Bioinformatics (Oxford, England) Sep 2, 2024
MOTIVATION: Automated machine learning (AutoML) solutions can bridge the gap between new computational advances and their real-world applications by enabling experimental scientists to build their own custom models. We examine different steps in the ...
Databases, Protein Peptides Computational Biology Software Algorithms Neural Networks, Computer Machine Learning
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NeoaPred: a deep-learning framework for predicting immunogenic neoantigen based on surface and structural features of peptide-human leukocyte antigen complexes.

Bioinformatics (Oxford, England) Sep 2, 2024
MOTIVATION: Neoantigens, derived from somatic mutations in cancer cells, can elicit anti-tumor immune responses when presented to autologous T cells by human leukocyte antigen. Identifying immunogenic neoantigens is crucial for cancer immunotherapy d...
Humans Neoplasms Peptides Software Histocompatibility Antigens Class I Antigens, Neoplasm Deep Learning HLA Antigens Computational Biology
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PEPerMINT: peptide abundance imputation in mass spectrometry-based proteomics using graph neural networks.

Bioinformatics (Oxford, England) Sep 1, 2024
MOTIVATION: Accurate quantitative information about protein abundance is crucial for understanding a biological system and its dynamics. Protein abundance is commonly estimated using label-free, bottom-up mass spectrometry (MS) protocols. Here, prote...
Mass Spectrometry Databases, Protein Peptides Proteomics Humans Software Neural Networks, Computer Algorithms
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Machine learning trims the peptide drug design process to a sweet spot.

Nature chemistry Sep 1, 2024
Humans Machine Learning Peptides Drug Design
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ACP-CapsPred: an explainable computational framework for identification and functional prediction of anticancer peptides based on capsule network.

Briefings in bioinformatics Jul 25, 2024
Cancer is a severe illness that significantly threatens human life and health. Anticancer peptides (ACPs) represent a promising therapeutic strategy for combating cancer. In silico methods enable rapid and accurate identification of ACPs without exte...
Antineoplastic Agents Computational Biology Databases, Protein Neoplasms Humans Peptides Neural Networks, Computer
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