Publications

@article{Lee2019,

title = {Pathogenic Protist Transmembranome database (PPTdb): A web-based platform for searching and analysis of protist transmembrane proteins},

author = {C. -C. Lee and P. -J. Huang and Y. -M. Yeh and S. -Y. Chen and C. -H. Chiu and W. -H. Cheng and P. Tang},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069785098&doi=10.1186%2fs12859-019-2857-7&partnerID=40&md5=a8d0bc61439150c3b7d52174c56420c4},

doi = {10.1186/s12859-019-2857-7},

issn = {14712105},

year  = {2019},

date = {2019-01-01},

journal = {BMC Bioinformatics},

volume = {20},

publisher = {BioMed Central Ltd.},

abstract = {Background: Pathogenic protist membrane transporter proteins play important roles not only in exchanging molecules into and out of cells but also in acquiring nutrients and biosynthetic compounds from their hosts. Currently, there is no centralized protist membrane transporter database published, which makes system-wide comparisons and studies of host-pathogen membranomes difficult to achieve. Results: We analyzed over one million protein sequences from 139 protists with full or partial genome sequences. Putative transmembrane proteins were annotated by primary sequence alignments, conserved secondary structural elements, and functional domains. We have constructed the PPTdb (Pathogenic Protist Transmembranome database), a comprehensive membrane transporter protein portal for pathogenic protists and their human hosts. The PPTdb is a web-based database with a user-friendly searching and data querying interface, including hierarchical transporter classification (TC) numbers, protein sequences, functional annotations, conserved functional domains, batch sequence retrieving and downloads. The PPTdb also serves as an analytical platform to provide useful comparison/mining tools, including transmembrane ability evaluation, annotation of unknown proteins, informative visualization charts, and iterative functional mining of host-pathogen transporter proteins. Conclusions: The PPTdb collected putative protist transporter proteins and offers a user-friendly data retrieving interface. Moreover, a pairwise functional comparison ability can provide useful information for identifying functional uniqueness of each protist. Finally, the host and non-host protein similarity search can fulfill the needs of comprehensive studies of protists and their hosts. The PPTdb is freely accessible at http://pptdb.cgu.edu.tw. © 2019 The Author(s).},

note = {cited By 0},

keywords = {Ability evaluation; Functional annotation; Functional domains; Secondary structural elements; Trans-membrane proteins; Transporter proteins; Web based platform; WEB-BASED database, amino acid sequence; article; genome; human; infectious agent; membrane; mining; nonhuman; protein domain; protist; sequence alignment; structure activity relation; computer interface; factual database; fungus; genetics; metabolism; plant, carrier protein, Classification (of information); Database systems; Query processing; Websites, Databases, Factual; Fungi; Humans; Membrane Transport Proteins; Plants; User-Computer Interface, Proteins},

pubstate = {published},

tppubtype = {article}

}

@article{Huang2018D964,

title = {MSignatureDB: A database for deciphering mutational signatures in human cancers},

author = {P. -J. Huang and L. -Y. Chiu and C. -C. Lee and Y. -M. Yeh and K. -Y. Huang and C. -H. Chiu and P. Tang},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040945094&doi=10.1093%2fnar%2fgkx1133&partnerID=40&md5=8a9d6d3a1fa21c1b8ae7f7acbf870b6a},

doi = {10.1093/nar/gkx1133},

issn = {03051048},

year  = {2018},

date = {2018-01-01},

journal = {Nucleic Acids Research},

volume = {46},

number = {D1},

pages = {D964-D970},

publisher = {Oxford University Press},

abstract = {Cancer is a genetic disease caused by somatic mutations; however, the understanding of the causative biological processes generating these mutations is limited. A cancer genome bears the cumulative effects of mutational processes during tumor development. Deciphering mutational signatures in cancer is a new topic in cancer research. The Wellcome Trust Sanger Institute (WTSI) has categorized 30 reference signatures in the COSMIC database based on the analyses of ∼410 000 sequencing datasets from TCGA and ICGC. Large cohorts and bioinformatics skills are required to perform the same analysis as WTSI. The quantification of known signatures in custom cohorts is not possible under the current framework of the COSMIC database, which motivates us to construct a database for mutational signatures in cancers and make such analyses more accessible to general researchers. mSignatureDB (http://tardis.cgu.edu.tw/msignaturedb) integrates R packages and in-house scripts to determine the contributions of the published signatures in 15 780 individual tumors from 73 TCGA/ICGC cancer projects, making comparison of signature patterns within and between projects become possible. mSignatureDB also allows users to perform signature analysis on their own datasets, quantifying contributions of signatures at sample resolution, which is a unique feature of mSignatureDB not available in other related databases. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.},

note = {cited By 26},

keywords = {Article; bioinformatics; cancer genetics; cancer research; gene sequence; genetic database; human; mutational analysis; priority journal; reference database; computer interface; genetics; mutation; neoplasm; nucleic acid database, Databases, Nucleic Acid; Humans; Mutation; Neoplasms; User-Computer Interface},

pubstate = {published},

tppubtype = {article}

}