Integrating machine learning to advance epitope mapping
S Grewal, N Hegde, SK Yanow - Frontiers in Immunology, 2024 - frontiersin.org
Identifying epitopes, or the segments of a protein that bind to antibodies, is critical for the
development of a variety of immunotherapeutics and diagnostics. In vaccine design, the …
development of a variety of immunotherapeutics and diagnostics. In vaccine design, the …
Machine learning to predict continuous protein properties from binary cell sorting data and map unseen sequence space
Proteins are a diverse class of biomolecules responsible for wide-ranging cellular functions,
from catalyzing reactions to recognizing pathogens. The ability to evolve proteins rapidly …
from catalyzing reactions to recognizing pathogens. The ability to evolve proteins rapidly …
Computational prediction of binding affinity for cdk2-ligand complexes. a protein target for cancer drug discovery
M Veit-Acosta… - Current Medicinal …, 2022 - benthamdirect.com
Background: CDK2 participates in the control of eukaryotic cell-cycle progression. Due to the
great interest in CDK2 for drug development and the relative easiness in crystallizing this …
great interest in CDK2 for drug development and the relative easiness in crystallizing this …
Modeling the sequence dependence of differential antibody binding in the immune response to infectious disease
R Chowdhury, AT Taguchi, L Kelbauskas… - PLoS computational …, 2023 - journals.plos.org
Past studies have shown that incubation of human serum samples on high density peptide
arrays followed by measurement of total antibody bound to each peptide sequence allows …
arrays followed by measurement of total antibody bound to each peptide sequence allows …
Predicting monoclonal antibody binding sequences from a sparse sampling of all possible sequences
P Bisarad, L Kelbauskas, A Singh, AT Taguchi… - Communications …, 2024 - nature.com
Previous work has shown that binding of target proteins to a sparse, unbiased sample of all
possible peptide sequences is sufficient to train a machine learning model that can then …
possible peptide sequences is sufficient to train a machine learning model that can then …
Highly heterogenous humoral immune response in Lyme disease patients revealed by broad machine learning-assisted antibody binding profiling with random …
L Kelbauskas, JB Legutki, NW Woodbury - Frontiers in Immunology, 2024 - frontiersin.org
Introduction Lyme disease (LD), a rapidly growing public health problem in the US,
represents a formidable challenge due to the lack of detailed understanding about how the …
represents a formidable challenge due to the lack of detailed understanding about how the …
Assessing sequence-based protein–protein interaction predictors for use in therapeutic peptide engineering
Engineering peptides to achieve a desired therapeutic effect through the inhibition of a
specific target activity or protein interaction is a non-trivial task. Few of the existing in silico …
specific target activity or protein interaction is a non-trivial task. Few of the existing in silico …
Machine Learning Model for Biomimetic Chromatography Peptide Ligands
JIB Janairo - ACS Applied Bio Materials, 2022 - ACS Publications
Purification is an essential part of antibody production, which are important therapeutic
biomolecules. Common methods of antibody purification rely on affinity chromatography …
biomolecules. Common methods of antibody purification rely on affinity chromatography …
Machine learning to predict continuous protein properties from simple binary sorting and deep sequencing data
Proteins are a diverse class of biomolecules responsible for wide-ranging cellular functions,
from catalyzing reactions and recognizing pathogens to forming dynamic cellular structure …
from catalyzing reactions and recognizing pathogens to forming dynamic cellular structure …
高通量多肽芯片及其应用
黄俊雄， 陶一敏， 钟佩， 赵春青， 李晓光， 王慧 - 上海预防医学, 2023 - sjpm.org.cn
本文介绍一种高通量分子筛选芯片——多肽芯片. 多肽芯片作为生物芯片的一种,
相比其他生物芯片, 有着易于制造合成, 探针性质稳定, 芯片探针通量高及信号特异性强等特点 …
相比其他生物芯片, 有着易于制造合成, 探针性质稳定, 芯片探针通量高及信号特异性强等特点 …