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Shanshan Zhang

Researcher at Temple University

Publications -  24
Citations -  1671

Shanshan Zhang is an academic researcher from Temple University. The author has contributed to research in topics: Computer science & Protein function prediction. The author has an hindex of 11, co-authored 22 publications receiving 1273 citations. Previous affiliations of Shanshan Zhang include Wuhan University.

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Journal ArticleDOI

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Yuxiang Jiang, +156 more
- 07 Sep 2016 - 
TL;DR: The second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function, was conducted by as mentioned in this paper. But the results of the CAFA2 assessment are limited.

Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Yuxiang Jiang, +146 more
TL;DR: The second critical assessment of functional annotation (CAFA) conducted, a timed challenge to assess computational methods that automatically assign protein function, revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies.
Journal ArticleDOI

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Naihui Zhou, +188 more
- 19 Nov 2019 - 
TL;DR: The third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed, concluded that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not.
Journal ArticleDOI

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Yuxiang Jiang, +145 more
TL;DR: The second Critical Assessment of Functional Annotation (CAFA) challenge as mentioned in this paper was the first attempt to assess computational methods that automatically assign protein function. And the results of CAFA2 showed that computational function prediction is improving.
Proceedings ArticleDOI

Independent Tasks Scheduling Based on Genetic Algorithm in Cloud Computing

TL;DR: Though GA is designed to solve combinatorial optimization problem, it's inefficient for global optimization, so this paper concludes with further researches in optimized genetic algorithm.