Xinping Yang

Prof. Xinping Yang


Research Focus & Metrics

Academic Career Length

27Years (2000-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 November 2014 in Cell
Verified
Journal Article
Closed access
TRThomas Rolland
Thomas Rolland
MTMurat Taşan
Murat Taşan
BCBenoit Charloteaux
Benoit Charloteaux
SPSamuel J. Pevzner
Samuel J. Pevzner
QZQuan Zhong
Quan Zhong
MVMarc Vidal
Marc Vidal

8 April 2020 in Nature
Verified
Journal Article
Closed access
PDF file
KLKatja Luck
Katja Luck
DKDae-Kyum Kim
Dae-Kyum Kim
LLLuke Lambourne
Luke Lambourne
KSKerstin Spirohn
Kerstin Spirohn
BBBridget E. Begg
Bridget E. Begg
MCMichael A. Calderwood
Michael A. Calderwood

1 April 2015 in Cell
Verified
Journal Article
Closed access
NSNidhi Sahni
Nidhi Sahni
SYSong Yi
Song Yi
MTMikko Taipale
Mikko Taipale
JBJuan I. Fuxman Bass
Juan I. Fuxman Bass
JCJasmin Coulombe-Huntington
Jasmin Coulombe-Huntington
MVMarc Vidal
Marc Vidal

26 June 2011 in Nature Methods
Verified
Journal Article
Open access
PDF file
XYXiaoping Yang
Xiaoping Yang
JBJesse S Boehm
Jesse S Boehm
XYXinping Yang
Xinping Yang
KSKourosh Salehi-Ashtiani
Kourosh Salehi-Ashtiani
THTong Hao
Tong Hao
DRDavid E Root
David E Root
Two sequence-verified, clonal, publicly available collections of human open reading frames are reported. One collection is in a lentiviral vector for expression in mammalian cells; the other is in the Gateway vector system. Functional characterization of the human genome requires tools for systematically modulating gene expression in both loss-of-function and gain-of-function experiments. We describe the production of a sequence-confirmed, clonal collection of over 16,100 human open-reading frames (ORFs) encoded in a versatile Gateway vector system. Using this ORFeome resource, we created a genome-scale expression collection in a lentiviral vector, thereby enabling both targeted experiments and high-throughput screens in diverse cell types.

1 February 2016 in Cell
Verified
Journal Article
Closed access
XYXinping Yang
Xinping Yang
JCJasmin Coulombe-Huntington
Jasmin Coulombe-Huntington
SKShuli Kang
Shuli Kang
GSGloria M. Sheynkman
Gloria M. Sheynkman
THTong Hao
Tong Hao
MVMarc Vidal
Marc Vidal

24 April 2011 in Nature Methods
Verified
Journal Article
Open access
PDF file
HYHaiyuan Yu
Haiyuan Yu
LTLeah Tardivo
Leah Tardivo
STStanley Tam
Stanley Tam
EWEvan Weiner
Evan Weiner
FGFana Gebreab
Fana Gebreab
MVMarc Vidal
Marc Vidal
A combination of PCR stitching with next-generation sequencing results in Stitch-seq, a massively parallel method for interactome mapping. The approach is applied to human protein-protein interactions assayed in yeast two-hybrid screens. Next-generation sequencing has not been applied to protein-protein interactome network mapping so far because the association between the members of each interacting pair would not be maintained in en masse sequencing. We describe a massively parallel interactome-mapping pipeline, Stitch-seq, that combines PCR stitching with next-generation sequencing and used it to generate a new human interactome dataset. Stitch-seq is applicable to various interaction assays and should help expand interactome network mapping.