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Items: 1 to 20 of 38

1.

Exploring the evolutionary dynamics of Rhizobium plasmids through bipartite network analysis.

Li X, Wang H, Tong W, Feng L, Wang L, Rahman SU, Wei G, Tao S.

Environ Microbiol. 2019 Jul 30. doi: 10.1111/1462-2920.14762. [Epub ahead of print]

PMID:
31361937
2.

Deciphering the rules of mRNA structure differentiation in Saccharomyces cerevisiae in vivo and in vitro with deep neural networks.

Yu H, Meng W, Mao Y, Zhang Y, Sun Q, Tao S.

RNA Biol. 2019 Aug;16(8):1044-1054. doi: 10.1080/15476286.2019.1612692. Epub 2019 May 23.

3.

CellSim: a novel software to calculate cell similarity and identify their co-regulation networks.

Li L, Che D, Wang X, Zhang P, Rahman SU, Zhao J, Yu J, Tao S, Lu H, Liao M.

BMC Bioinformatics. 2019 Mar 4;20(1):111. doi: 10.1186/s12859-019-2699-3.

4.

Evolutionary Analysis of the F-Box Gene Family in Saccharomycetaceae.

Yao M, Rahman SU, Wang A, Ma T, Raza SHA, Mehmood R, Liu Y, Tao S.

DNA Cell Biol. 2019 Apr;38(4):333-340. doi: 10.1089/dna.2018.4271. Epub 2019 Feb 25.

PMID:
30801225
5.

Rapid Identification of Major QTLS Associated With Near- Freezing Temperature Tolerance in Saccharomyces cerevisiae.

Feng L, Jia H, Qin Y, Song Y, Tao S, Liu Y.

Front Microbiol. 2018 Sep 11;9:2110. doi: 10.3389/fmicb.2018.02110. eCollection 2018.

6.

A Novel Strategy for Detecting Recent Horizontal Gene Transfer and Its Application to Rhizobium Strains.

Li X, Tong W, Wang L, Rahman SU, Wei G, Tao S.

Front Microbiol. 2018 May 15;9:973. doi: 10.3389/fmicb.2018.00973. eCollection 2018.

7.

miRNA editing landscape reveals miR-34c regulated spermatogenesis through structure and target change in pig and mouse.

Wang X, Zhang P, Li L, Che D, Li T, Li H, Li Q, Jia H, Tao S, Hua J, Zeng W, Liao M.

Biochem Biophys Res Commun. 2018 Aug 25;502(4):486-492. doi: 10.1016/j.bbrc.2018.05.197. Epub 2018 Jun 5.

PMID:
29864426
8.

Genomic insight into the taxonomy of Rhizobium genospecies that nodulate Phaseolus vulgaris.

Tong W, Li X, Huo Y, Zhang L, Cao Y, Wang E, Chen W, Tao S, Wei G.

Syst Appl Microbiol. 2018 Jul;41(4):300-310. doi: 10.1016/j.syapm.2018.03.001. Epub 2018 Mar 16.

PMID:
29576402
9.

Analysis of codon usage bias of Crimean-Congo hemorrhagic fever virus and its adaptation to hosts.

Rahman SU, Yao X, Li X, Chen D, Tao S.

Infect Genet Evol. 2018 Mar;58:1-16. doi: 10.1016/j.meegid.2017.11.027. Epub 2017 Dec 6.

PMID:
29198972
10.

Codon usage bias in 5' terminal coding sequences reveals distinct enrichment of gene functions.

Liu H, Rahman SU, Mao Y, Xu X, Tao S.

Genomics. 2017 Oct;109(5-6):506-513. doi: 10.1016/j.ygeno.2017.07.008. Epub 2017 Aug 1.

11.

Dynamic and modular gene regulatory networks drive the development of gametogenesis.

Che D, Wang Y, Bai W, Li L, Liu G, Zhang L, Zuo Y, Tao S, Hua J, Liao M.

Brief Bioinform. 2017 Jul 1;18(4):712-721. doi: 10.1093/bib/bbw056.

PMID:
27373733
12.

Codon Usage in Signal Sequences Affects Protein Expression and Secretion Using Baculovirus/Insect Cell Expression System.

Wang Y, Mao Y, Xu X, Tao S, Chen H.

PLoS One. 2015 Dec 23;10(12):e0145887. doi: 10.1371/journal.pone.0145887. eCollection 2015.

13.
14.

Influences of dominance and evolution of sex in finite diploid populations.

Chang Y, Hua Y, Jiang X, Tao S.

PLoS One. 2015 May 26;10(5):e0128459. doi: 10.1371/journal.pone.0128459. eCollection 2015.

15.

Genome-wide identification and evolution of HECT genes in soybean.

Meng X, Wang C, Rahman SU, Wang Y, Wang A, Tao S.

Int J Mol Sci. 2015 Apr 16;16(4):8517-35. doi: 10.3390/ijms16048517.

16.

Neighbor preferences of amino acids and context-dependent effects of amino acid substitutions in human, mouse, and dog.

Fu M, Huang Z, Mao Y, Tao S.

Int J Mol Sci. 2014 Sep 10;15(9):15963-80. doi: 10.3390/ijms150915963.

17.

Evolution of the F-box gene family in Euarchontoglires: gene number variation and selection patterns.

Wang A, Fu M, Jiang X, Mao Y, Li X, Tao S.

PLoS One. 2014 Apr 11;9(4):e94899. doi: 10.1371/journal.pone.0094899. eCollection 2014.

18.

Deciphering the rules by which dynamics of mRNA secondary structure affect translation efficiency in Saccharomyces cerevisiae.

Mao Y, Liu H, Liu Y, Tao S.

Nucleic Acids Res. 2014 Apr;42(8):4813-22. doi: 10.1093/nar/gku159. Epub 2014 Feb 21.

19.

Training set selection for the prediction of essential genes.

Cheng J, Xu Z, Wu W, Zhao L, Li X, Liu Y, Tao S.

PLoS One. 2014 Jan 22;9(1):e86805. doi: 10.1371/journal.pone.0086805. eCollection 2014.

20.

A new computational strategy for predicting essential genes.

Cheng J, Wu W, Zhang Y, Li X, Jiang X, Wei G, Tao S.

BMC Genomics. 2013 Dec 21;14:910. doi: 10.1186/1471-2164-14-910.

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