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ACC descriptors performance.

NIAID Data Ecosystem2026-03-07 收录

氨基酸描述符评估

生物信息学分类

数据链接：

https://figshare.com/articles/dataset/_ACC_descriptors_performance_/789433 数据链接链接失效反馈

官方服务：

资源简介：

The maximum MCC value, corresponding to the optimal feature set, was compared for each encoding.

应用场景：

创建时间：

2013-09-05

蛋白质预测

生物信息学分类

Sn: Sensitivity; Sp: Specificity; Acc: Accuracy; MCC: Matthew’s Correlation Coefficient. Performance of SVM based models using amino acid composition as input feature on nine terminus datasets.

NIAID Data Ecosystem70

Candidate genes sorted by biological function.

基因功能注释

生物信息学分类

Only the genes that are unambiguously identified are mentioned in this table.

NIAID Data Ecosystem40

Classification and distribution of neuraminidase homologs into four statistically significant subgroups by Zebra2.

病毒酶学分析

生物信息学分类

Classification and distribution of neuraminidase homologs into four statistically significant subgroups by Zebra2.

NIAID Data Ecosystem20

Comparison between Mirident and previously published software/algorithms.

microRNA前体识别

生物信息学分类

1Original training data. 2“Th” indicates “Threshold”. All the models were tested on the same data set of 124 pre-miRNAs and 124 non-pre-miRNA hairpins.

NIAID Data Ecosystem40

The European Nucleotide Archive (ENA) taxonomy

生物信息学分类

核苷酸序列注释

The classification system for source biological organisms for all INSDC records is the NCBI Taxonomy. The ENA team work alongside taxonomists at the NCBI to ensure that all ENA records display the acc

GBIF2021-03-11 更新30

ACC descriptors performance.

资源简介：

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