Recent progress in protein subcellular location prediction.

By Kuo-Chen Chou, Hongbin Shen. Analytical Biochemistry, 2007

752 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/fce71ae4be65625191df38de722f245882ddb7ff

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In Molecular Biology

Citations in the corpus

MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction (2009, methodology): “GO terms were previously combined with sequence-based information in the form of pseudo amino acid composition in a group of predictors [36,37].”
iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudo k-tuple nucleotide composition (2016, methodology): “To make the prediction method not only able to identify whether a DNA sample is an enhancer but also make it able to identify the strength type, here we are to develop a two-layer predictor similar to the treatment in identifying membrane proteins and their types (Chou and Shen, 2007a,b).”
Some remarks on protein attribute prediction and pseudo amino acid composition (2010, methodology): “Accordingly, protein samples deﬁned in a GO database space would be clustered in a way better reﬂecting some of their important attributes, such as subcellular localization and biological function (Chou and Shen, 2007c, 2008b).”
iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition (2014, background): “(ii) No cutoff threshold (26) was imposed to winnow the redundant samples or those with high sequence similarity with others in a same subset data set.”
Identifying Sigma70 Promoters with Novel Pseudo Nucleotide Composition (2019, background): “nucleosome occupancy [17], the formation of chromosomes [18], research on meiotic recombination [19], and so on.”
PseKNC: a flexible web server for generating pseudo K-tuple nucleotide composition. (2014, neutral): “(9) can be written as [35]”