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List of deep learning-based MHC-peptide binding prediction tools.

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数据链接：

https://figshare.com/articles/dataset/List_of_deep_learning-based_MHC-peptide_binding_prediction_tools_/28145294 数据链接链接失效反馈

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资源简介：

List of deep learning-based MHC-peptide binding prediction tools.

应用场景：

创建时间：

2025-01-06

疫苗候选物筛选

免疫信息学

Visceral leishmaniasis (VL), also known as kala-azar, is the most dangerous form of leishmaniasis. Currently no effective vaccine is available for clinical use. Since the pathogenicity of different Le

NIAID Data Ecosystem60

Additional file 5 of FungalRV: adhesin prediction and immunoinformatics portal for human fungal pathogens

真菌病原体粘附素预测

免疫信息学

Additional file 5:"FungalRV adhesin predictor" scores of In-silico predicted adhesins by Weig et al. "FungalRV adhesin predictor" scores of In-silico predicted adhesins by Weig et al. are listed in th

NIAID Data Ecosystem20

Conformational B-cell epitopes from 3D MEV construct protein predicted by ElliPro server.

免疫信息学

抗原表位预测

Conformational B-cell epitopes from 3D MEV construct protein predicted by ElliPro server.

NIAID Data Ecosystem00

Antigenic peptides of TbLysoPLA and TbGK predicted using BepiPred-2.0 prediction.

抗原表位

免疫信息学

Antigenic peptides of TbLysoPLA and TbGK predicted using BepiPred-2.0 prediction.

NIAID Data Ecosystem30

Epitope prediction for MHC B4, B15, B19 and B21 based on anchor residues.

MHC表位预测

免疫信息学

Predicted epitopes and their localization based on anchor residues that have been described for B4, B15, B19 and B21 [32]–[34]. X represents any amino acid. Anchor residues specific for the different

NIAID Data Ecosystem20

List of deep learning-based MHC-peptide binding prediction tools.

资源简介：

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