AUC values for the three methods evaluated on MHCBN-SRDS2 datasets.

Figshare2015-12-02 更新2026-05-11 收录

数据链接：

https://figshare.com/articles/dataset/_AUC_values_for_the_three_methods_evaluated_on_MHCBN_SRDS2_datasets_/591363 数据链接链接失效反馈

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For each dataset, the rank of each classifier is shown in parentheses.

创建时间：

2015-12-02

Performance characteristics of the classifier.

医学诊断分类

分类器性能评估

1Held out dataset were annotated at report level only as being positive, negative or equivocal for IMD. Abbreviations: TN, true positives; FP, false positives; TN, true negatives; FN, false negatives;

NIAID Data Ecosystem90

Metrics characterizing the classification performance of individual signatures as a function of the classifier and acoustic set used.

声学签名分类

分类器性能评估

Four metrics are reported: log loss, AUC, balanced accuracy, and accuracy. The best performance achieved by a primary configuration (upper part) and an ensemble configuration (lower part) is displayed

NIAID Data Ecosystem50

5-fold cross-validation performance and statistical comparison between CatBoost and Logistic regression models.

机器学习模型比较

分类器性能评估

5-fold cross-validation performance and statistical comparison between CatBoost and Logistic regression models.

NIAID Data Ecosystem20

Additional file 3: of NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets

MHC-肽结合预测

Allele-specific length preference for 24 MHC molecules characterized by 20 or more ligand data points for the allmer and 9mer prediction methods compared to the length preference in the SYFPEITHI data

Figshare2016-12-15 更新60

Peptides from human cyclin D1-a that are predicted to bind to HLA-DR.B1 and embedded short peptides (in italics) that bind to HLA-A0201 molecules.

MHC-肽结合预测

免疫表位预测

*SYFPEITHI prediction software was used for HLA-DR.B1-binding prediction. Each epitope has different binding affinity to various DR.B1 subtypes, which was summarized as the range of binding scores. RA

NIAID Data Ecosystem50

AUC values for the three methods evaluated on MHCBN-SRDS2 datasets.

资源简介：

相关数据集