Machine learning models for predicting cytotoxicity of nanomaterials
The wide application of nanomaterials in consumer and medical products has raised
concerns about their potential adverse effects on human health. Thus, more and more …
concerns about their potential adverse effects on human health. Thus, more and more …
Molecular dynamics simulations and applications in computational toxicology and nanotoxicology
Nanotoxicology studies toxicity of nanomaterials and has been widely applied in biomedical
researches to explore toxicity of various biological systems. Investigating biological systems …
researches to explore toxicity of various biological systems. Investigating biological systems …
Genome sequencing of the sweetpotato whitefly Bemisia tabaci MED/Q
W Xie, C Chen, Z Yang, L Guo, X Yang, D Wang… - …, 2017 - academic.oup.com
The sweetpotato whitefly Bemisia tabaci is a highly destructive agricultural and ornamental
crop pest. It damages host plants through both phloem feeding and vectoring plant …
crop pest. It damages host plants through both phloem feeding and vectoring plant …
HLA class I binding prediction via convolutional neural networks
Motivation Many biological processes are governed by protein–ligand interactions. One
such example is the recognition of self and non-self cells by the immune system. This …
such example is the recognition of self and non-self cells by the immune system. This …
PSSMHCpan: a novel PSSM-based software for predicting class I peptide-HLA binding affinity
G Liu, D Li, Z Li, S Qiu, W Li, C Chao, N Yang… - Giga …, 2017 - academic.oup.com
Predicting peptide binding affinity with human leukocyte antigen (HLA) is a crucial step in
developing powerful antitumor vaccine for cancer immunotherapy. Currently available …
developing powerful antitumor vaccine for cancer immunotherapy. Currently available …
DeepNetBim: deep learning model for predicting HLA-epitope interactions based on network analysis by harnessing binding and immunogenicity information
Background Epitope prediction is a useful approach in cancer immunology and
immunotherapy. Many computational methods, including machine learning and network …
immunotherapy. Many computational methods, including machine learning and network …
Adverse drug reactions triggered by the common HLA-B* 57: 01 variant: a molecular docking study
G Van Den Driessche, D Fourches - Journal of cheminformatics, 2017 - Springer
Background Human leukocyte antigen (HLA) surface proteins are directly involved in
idiosyncratic adverse drug reactions. Herein, we present a structure-based analysis of the …
idiosyncratic adverse drug reactions. Herein, we present a structure-based analysis of the …
Machine learning methods for predicting HLA-peptide binding activity
As major histocompatibility complexes in humans, the human leukocyte antigens (HLAs)
have important functions to present antigen peptides onto T-cell receptors for immunological …
have important functions to present antigen peptides onto T-cell receptors for immunological …
A rapid, non-invasive method for fatigue detection based on voice information
X Gao, K Ma, H Yang, K Wang, B Fu, Y Zhu… - Frontiers in Cell and …, 2022 - frontiersin.org
Fatigue results from a series of physiological and psychological changes due to continuous
energy consumption. It can affect the physiological states of operators, thereby reducing …
energy consumption. It can affect the physiological states of operators, thereby reducing …
In silico pipeline to identify tumor-specific antigens for cancer immunotherapy using exome sequencing data
D Morazán-Fernández, J Mora, JA Molina-Mora - Phenomics, 2023 - Springer
Tumor-specific antigens or neoantigens are peptides that are expressed only in cancer cells
and not in healthy cells. Some of these molecules can induce an immune response, and …
and not in healthy cells. Some of these molecules can induce an immune response, and …