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Systematic proteome and proteostasis profiling in human Trisomy 21 fibroblast cells. Nature Communications 2017, 8:1212.\\\",\\\"@context\\\":\\\"http://schema.org\\\"}\"},{\"schemaName\":\"MedicalScholarlyArticle\",\"jsonData\":\"{\\\"@type\\\":\\\"MedicalScholarlyArticle\\\",\\\"publicationType\\\":\\\"Journal Article\\\",\\\"inLanguage\\\":\\\"en-US\\\",\\\"headline\\\":\\\"On the Dependency of Cellular Protein Levels on mRNA Abundance.\\\",\\\"url\\\":\\\"https://www.ncbi.nlm.nih.gov/pubmed/27104977\\\",\\\"author\\\":[{\\\"@type\\\":\\\"Person\\\",\\\"mainEntityOfPage\\\":{\\\"@type\\\":\\\"WebPage\\\",\\\"@id\\\":\\\"https://medicine.yale.edu/ysm/profile/yansheng_liu/\\\",\\\"@context\\\":\\\"http://schema.org\\\"},\\\"name\\\":\\\"Yansheng Liu\\\",\\\"description\\\":\\\"Dr. Liu received his PhD of Biomedical Sciences at Shanghai Institute for Biological Sciences, Chinese Academy of Sciences. 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Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS. Nature Biotechnology 2017, 35:781-788.\\\",\\\"@context\\\":\\\"http://schema.org\\\"}\"},{\"schemaName\":\"MedicalScholarlyArticle\",\"jsonData\":\"{\\\"@type\\\":\\\"MedicalScholarlyArticle\\\",\\\"publicationType\\\":\\\"Journal Article\\\",\\\"inLanguage\\\":\\\"en-US\\\",\\\"headline\\\":\\\"A Class of Environmental and Endogenous Toxins Induces BRCA2 Haploinsufficiency and Genome Instability.\\\",\\\"url\\\":\\\"https://www.ncbi.nlm.nih.gov/pubmed/28575672\\\",\\\"author\\\":[{\\\"@type\\\":\\\"Person\\\",\\\"mainEntityOfPage\\\":{\\\"@type\\\":\\\"WebPage\\\",\\\"@id\\\":\\\"https://medicine.yale.edu/ysm/profile/yansheng_liu/\\\",\\\"@context\\\":\\\"http://schema.org\\\"},\\\"name\\\":\\\"Yansheng Liu\\\",\\\"description\\\":\\\"Dr. Liu received his PhD of Biomedical Sciences at Shanghai Institute for Biological Sciences, Chinese Academy of Sciences. 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A Class of Environmental and Endogenous Toxins Induces BRCA2 Haploinsufficiency and Genome Instability. Cell 2017, 169:1105-1118.e15.\\\",\\\"@context\\\":\\\"http://schema.org\\\"}\"},{\"schemaName\":\"MedicalScholarlyArticle\",\"jsonData\":\"{\\\"@type\\\":\\\"MedicalScholarlyArticle\\\",\\\"publicationType\\\":\\\"Journal Article\\\",\\\"inLanguage\\\":\\\"en-US\\\",\\\"headline\\\":\\\"Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectro\\\",\\\"url\\\":\\\"https://www.ncbi.nlm.nih.gov/pubmed/28827567\\\",\\\"author\\\":[{\\\"@type\\\":\\\"Person\\\",\\\"mainEntityOfPage\\\":{\\\"@type\\\":\\\"WebPage\\\",\\\"@id\\\":\\\"https://medicine.yale.edu/ysm/profile/yansheng_liu/\\\",\\\"@context\\\":\\\"http://schema.org\\\"},\\\"name\\\":\\\"Yansheng Liu\\\",\\\"description\\\":\\\"Dr. Liu received his PhD of Biomedical Sciences at Shanghai Institute for Biological Sciences, Chinese Academy of Sciences. 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Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry. Nature Communications 2017, 8:291.\\\",\\\"@context\\\":\\\"http://schema.org\\\"}\"},{\"schemaName\":\"MedicalScholarlyArticle\",\"jsonData\":\"{\\\"@type\\\":\\\"MedicalScholarlyArticle\\\",\\\"publicationType\\\":\\\"Journal Article\\\",\\\"inLanguage\\\":\\\"en-US\\\",\\\"headline\\\":\\\"Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition an\\\",\\\"url\\\":\\\"https://www.ncbi.nlm.nih.gov/pubmed/28825704\\\",\\\"author\\\":[{\\\"@type\\\":\\\"Person\\\",\\\"mainEntityOfPage\\\":{\\\"@type\\\":\\\"WebPage\\\",\\\"@id\\\":\\\"https://medicine.yale.edu/ysm/profile/yansheng_liu/\\\",\\\"@context\\\":\\\"http://schema.org\\\"},\\\"name\\\":\\\"Yansheng Liu\\\",\\\"description\\\":\\\"Dr. Liu received his PhD of Biomedical Sciences at Shanghai Institute for Biological Sciences, Chinese Academy of Sciences. 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Comparison of targeted proteomics approaches for detecting and quantifying proteins derived from human cancer tissues. Proteomics 2017, 17.\\\",\\\"@context\\\":\\\"http://schema.org\\\"}\"},{\"schemaName\":\"MedicalScholarlyArticle\",\"jsonData\":\"{\\\"@type\\\":\\\"MedicalScholarlyArticle\\\",\\\"publicationType\\\":\\\"Journal Article\\\",\\\"inLanguage\\\":\\\"en-US\\\",\\\"headline\\\":\\\"Protein kinase D at the Golgi controls NLRP3 inflammasome activation.\\\",\\\"url\\\":\\\"https://www.ncbi.nlm.nih.gov/pubmed/28716882\\\",\\\"author\\\":[{\\\"@type\\\":\\\"Person\\\",\\\"mainEntityOfPage\\\":{\\\"@type\\\":\\\"WebPage\\\",\\\"@id\\\":\\\"https://medicine.yale.edu/ysm/profile/yansheng_liu/\\\",\\\"@context\\\":\\\"http://schema.org\\\"},\\\"name\\\":\\\"Yansheng Liu\\\",\\\"description\\\":\\\"Dr. Liu received his PhD of Biomedical Sciences at Shanghai Institute for Biological Sciences, Chinese Academy of Sciences. 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Glycoproteomic analysis of prostate cancer tissues by SWATH mass spectrometry discovers N-acylethanolamine acid amidase and protein tyrosine kinase 7 as signatures for tumor aggressiveness. 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Integrative proteomics and tissue microarray profiling indicate the association between overexpressed serum proteins and non-small cell lung cancer. 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Shotgun and targeted proteomics reveal that pre-surgery serum levels of LRG1, SAA, and C4BP may refine prognosis of resected squamous cell lung cancer. 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Dr. Liu received his PhD of Biomedical Sciences at Shanghai Institute for Biological Sciences, Chinese Academy of Sciences. Dr. Liu completed a post-doctoral research fellowship (May 2011 - October 2017) in the Proteomics Laboratory of Dr. Ruedi Aebersold in the Institute of Molecular Systems Biology, ETH Zurich, Switzerland. Dr. Liu joined Yale Cancer Biology Institute as an Assistant Professor of Pharmacology in December 2017. His research group at Yale aims to contribute to the development of Data independent acquisition (DIA) mass spectrometry and other proteomic techniques and their applications in Cancer Biology and Systems Biology studies.

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Current research:

Copy number alterations (CNAs) of specific genes, whole chromosomes (Chr), or parts thereof are a major cause of various diseases and developmental abnormalities. Indeed, aneuploidy occurs in 88% of cancers. Gene expression analysis helps in understanding how CNA and aneuploidy cause detrimental phenotypes. In a simple “on-target” model, the increased CNAs may lead to higher gene expression, and vise versa. However, CNAs also affect the expression of genes located outside the duplication/deletion region itself via indirect mechanisms, namely “off-target” effect. Based on emerging literature including ours, we argue that it is indispensable and imperative to measure the proteins, but not only the mRNAs, for understanding de facto CNA/aneuploidy consequence.

A major goal of our research is to study CNA/aneuploidy consequences by the usage of isogenic biological models and state-of-the-art quantitative mass spectrometry (MS).

Previous contribution:

Biologically, my previous research contributed to understanding of human “genotype-phenotype” association by characterizing proteome dosage. I performed the systematic quantification of genetic and post-transcriptional control of proteome through dosage and turnover, i.e., “proteotype” analysis. With very cautious design that uses isogenic samples for removing individual genomic variability, I accomplished several studies demonstrating the importance and mechanisms of protein-level control in humans. a) I quantified the different contribution from genetics, environment, and aging process in controlling 342 plasma proteins using 232 human healthy twins, which was widely discussed as a landmark study for blood proteomics, and mentioned at Science. b) We reported the strong quantitative contribution from alternative splicing on human proteome, which was highlighted in Nature Methods. c) We analyzed the primary fetal skin fibroblasts derived from a pair of monozygotic twins discordant for Trisomy 21 and genetically unrelated individuals, and reported proteostatsis mechanisms against aneuploidy through stoichiometry of protein complex and confinements of specific organelles. This paper was widely reported in media. d) Using HeLa cell lines from 13 labs, we quantified complex, non-linear response of the cells to genomic variability across the transcriptome and proteotype. This paper was published at Nature Biotechnology. The data indicates a striking degree of genomic variability and its complex translation into distinctive proteotypic and phenotypic patterns. Together, these papers provided new dimensions for understanding protein expression in diseases.

Technically, my previous research contributed to the development of DIA-MS (or, SWATH-MS in many papers) technique. These methods showed great potential and impact in proteomics field. With SWATH-MS emerged in proteomics, the last 6 years witnessed significant methodology paradigm shift from conventional shotgun proteomics to DIA. I was one of the core members of SWATH team and contributed significantly to its method (e.g., variable windows, cross-lab optimization), bioinformatics (e.g., TRIC for multi-sample alignment, IPF for large-scale PTM analysis, panHuman library for human protein identification), and quality control (e.g., in clinical tissue/ plasma materials). These publications are widely cited and referenced (highlighted in Nature Methods three times).

Long-term interest:

My long-term scientific interest is to investigate the translational and post-translational mechanisms underlying the development of human genetic disease and cancer phenotypes. The core component of my scientific goal focuses on the basic research investigating how the living cells organize its protein dosage, dynamics, turnover through protein complex stoichiometry control, protein-protein interaction, and protein sub-cellular localization to react against genetic variability and aberrations such as chromosomal abnormality.

Other general research interests in collaborative studies: 1) Protein localization and mis-localization in diseases. 2) The interaction between genetics and proteomics and the correlation between mRNAs and proteins. 3) Development of cutting-edge, hybrid MS-based proteomic techniques and bioinformatic solutions. 4) Personalized medicine and biomarker discovery.

Genetics - Translational and Post-Translational Levels; Cancer biology; Cancer proteomics; Biomarker discovery

\",\"summary\":\"

\\\"Proteome translates the code of life into diversity. We hope to understand the fundamental rules of proteomics. \\\"

The Liu laboratory works on the development of the state-of-the-art mass spectrometry method named DIA-MS (Liu Y. et al, Cell 2016) (Liu Y. et al, Nature Biotechnology 2019) and the application into different systems. These systems include, for example, the blood proteome of human monozygotic twins (Liu Y. et al, Molecular Systems Biology 2015), the phosphoproteomic signaling (Rosenberger R.*, Liu Y.* et al, Nature Biotechnology 2017), human genetic disorder (Liu Y. et al, Nature Communications 2017), RNA alternative splicing (Liu Y. et al, Cell Reports 2017).

The current major scientific focuses in Liu lab are cancer aneuploidy (Liu Y. et al, Nature Biotechnology 2019) and cancer signaling transduction (Salvoska B...Liu Y, Molecular Systems Biology 2020). Altogether, Dr. Liu's group is especially interested in revealing the impact of genetics at the translational and post-translational levels for cancer studies.

\",\"researchInterests\":[\"Mass Spectrometry\"],\"healthInterests\":[],\"researchImagesGallery\":{\"title\":null,\"items\":[{\"galleryItemType\":\"image\",\"data\":{\"title\":\"Proteomics based on DIA MS\",\"caption\":\"The next-generation proteomics, such as Data Independent Acquisition (DIA) based mass spectrometry, features the\\nhighly reproducible and precise quantification at MS2- level using signal traces presented as peak groups along liquid chromatography\\ngradient. With such measurements, signal transduction can be profiled under various scenarios, such as steady state, long-term state\\nchanges, and short-term adaptation [1]. Questions like how protein abundance, phosphorylation, and turnover response longitudinally to\\ndifferent pharmacological interventions can be addressed.\\n[1] Liu Y et al., (2016) Cell 165: 535-550\",\"credit\":null,\"illustrationCredit\":null,\"url\":\"https://ysm-res.cloudinary.com/image/upload/v1/yms/prod/7ca50b57-180a-4236-bbfd-89edad5c197c\",\"altText\":\"Proteomics based on DIA MS\",\"width\":1743,\"height\":1596,\"imageVariants\":[]}}]}},\"publications\":[{\"title\":\"Isoform-resolved correlation analysis between mRNA abundance regulation and protein level degradation.\",\"citation\":\"Salovska B, Zhu H, Gandhi T, Frank M, Li W, Rosenberger G, Wu C, Germain PL, Zhou H, Hodny Z, Reiter L, Liu Y. Isoform-resolved correlation analysis between mRNA abundance regulation and protein level degradation. Molecular Systems Biology 2020, 16:e9170.\",\"year\":2020,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/32175694\",\"text\":\"Isoform-resolved correlation analysis between mRNA abundance regulation and protein level degradation.\"}},{\"title\":\"NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses.\",\"citation\":\"Wang S, Li W, Hu L, Cheng J, Yang H, Liu Y. NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses. Nucleic Acids Research 2020.\",\"year\":2020,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/32526036\",\"text\":\"NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses.\"}},{\"title\":\"Germ-free and microbiota-associated mice yield small intestinal epithelial organoids with equivalent and robust transcriptome/proteome expression phenotypes.\",\"citation\":\"Hausmann A, Russo G, Grossmann J, Zünd M, Schwank G, Aebersold R, Liu Y, Sellin ME, Hardt WD. Germ-free and microbiota-associated mice yield small intestinal epithelial organoids with equivalent and robust transcriptome/proteome expression phenotypes. Cellular Microbiology 2020, 22:e13191.\",\"year\":2020,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/32068945\",\"text\":\"Germ-free and microbiota-associated mice yield small intestinal epithelial organoids with equivalent and robust transcriptome/proteome expression phenotypes.\"}},{\"title\":\"A Global Screen for Assembly State Changes of the Mitotic Proteome by SEC-SWATH-MS.\",\"citation\":\"Heusel M, Frank M, Köhler M, Amon S, Frommelt F, Rosenberger G, Bludau I, Aulakh S, Linder MI, Liu Y, Collins BC, Gstaiger M, Kutay U, Aebersold R. A Global Screen for Assembly State Changes of the Mitotic Proteome by SEC-SWATH-MS. Cell Systems 2020, 10:133-155.e6.\",\"year\":2020,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/32027860\",\"text\":\"A Global Screen for Assembly State Changes of the Mitotic Proteome by SEC-SWATH-MS.\"}},{\"title\":\"Multi-in-One: Multiple-Proteases, One-Hour-Shot Strategy for Fast and High-Coverage Phosphoproteomic Investigation.\",\"citation\":\"Gao XJ, Li QR, Liu Y, Zeng R. Multi-in-One: Multiple-Proteases, One-Hour-Shot Strategy for Fast and High-Coverage Phosphoproteomic Investigation. Analytical Chemistry 2020, 92:8943-8951.\",\"year\":2020,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/32479063\",\"text\":\"Multi-in-One: Multiple-Proteases, One-Hour-Shot Strategy for Fast and High-Coverage Phosphoproteomic Investigation.\"}},{\"title\":\"Assessing the Relationship Between Mass Window Width and Retention Time Scheduling on Protein Coverage for Data-Independent Acquisition.\",\"citation\":\"Li W, Chi H, Salovska B, Wu C, Sun L, Rosenberger G, Liu Y. Assessing the Relationship Between Mass Window Width and Retention Time Scheduling on Protein Coverage for Data-Independent Acquisition. Journal Of The American Society For Mass Spectrometry 2019, 30:1396-1405.\",\"year\":2019,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/31147889\",\"text\":\"Assessing the Relationship Between Mass Window Width and Retention Time Scheduling on Protein Coverage for Data-Independent Acquisition.\"}},{\"title\":\"Combining Rapid Data Independent Acquisition and CRISPR Gene Deletion for Studying Potential Protein Functions: A Case of HMGN1.\",\"citation\":\"Mehnert M, Li W, Wu C, Salovska B, Liu Y. Combining Rapid Data Independent Acquisition and CRISPR Gene Deletion for Studying Potential Protein Functions: A Case of HMGN1. Proteomics 2019, 19:e1800438.\",\"year\":2019,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/30901150\",\"text\":\"Combining Rapid Data Independent Acquisition and CRISPR Gene Deletion for Studying Potential Protein Functions: A Case of HMGN1.\"}},{\"title\":\"Multi-omic measurements of heterogeneity in HeLa cells across laboratories.\",\"citation\":\"Liu Y, Mi Y, Mueller T, Kreibich S, Williams EG, Van Drogen A, Borel C, Frank M, Germain PL, Bludau I, Mehnert M, Seifert M, Emmenlauer M, Sorg I, Bezrukov F, Bena FS, Zhou H, Dehio C, Testa G, Saez-Rodriguez J, Antonarakis SE, Hardt WD, Aebersold R. Multi-omic measurements of heterogeneity in HeLa cells across laboratories. Nature Biotechnology 2019, 37:314-322.\",\"year\":2019,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/30778230\",\"text\":\"Multi-omic measurements of heterogeneity in HeLa cells across laboratories.\"}},{\"title\":\"Integrated Proteogenomic Characterization of HBV-Related Hepatocellular Carcinoma.\",\"citation\":\"Gao Q, Zhu H, Dong L, Shi W, Chen R, Song Z, Huang C, Li J, Dong X, Zhou Y, Liu Q, Ma L, Wang X, Zhou J, Liu Y, Boja E, Robles AI, Ma W, Wang P, Li Y, Ding L, Wen B, Zhang B, Rodriguez H, Gao D, Zhou H, Fan J. Integrated Proteogenomic Characterization of HBV-Related Hepatocellular Carcinoma. Cell 2019, 179:561-577.e22.\",\"year\":2019,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/31585088\",\"text\":\"Integrated Proteogenomic Characterization of HBV-Related Hepatocellular Carcinoma.\"}},{\"title\":\"Impact of Alternative Splicing on the Human Proteome.\",\"citation\":\"Liu Y, Gonzàlez-Porta M, Santos S, Brazma A, Marioni JC, Aebersold R, Venkitaraman AR, Wickramasinghe VO. Impact of Alternative Splicing on the Human Proteome. Cell Reports 2017, 20:1229-1241.\",\"year\":2017,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/28768205\",\"text\":\"Impact of Alternative Splicing on the Human Proteome.\"}},{\"title\":\"Systematic proteome and proteostasis profiling in human Trisomy 21 fibroblast cells.\",\"citation\":\"Liu Y, Borel C, Li L, Müller T, Williams EG, Germain PL, Buljan M, Sajic T, Boersema PJ, Shao W, Faini M, Testa G, Beyer A, Antonarakis SE, Aebersold R. Systematic proteome and proteostasis profiling in human Trisomy 21 fibroblast cells. Nature Communications 2017, 8:1212.\",\"year\":2017,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/29089484\",\"text\":\"Systematic proteome and proteostasis profiling in human Trisomy 21 fibroblast cells.\"}},{\"title\":\"On the Dependency of Cellular Protein Levels on mRNA Abundance.\",\"citation\":\"Liu Y, Beyer A, Aebersold R. On the Dependency of Cellular Protein Levels on mRNA Abundance. Cell 2016, 165:535-50.\",\"year\":2016,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/27104977\",\"text\":\"On the Dependency of Cellular Protein Levels on mRNA Abundance.\"}},{\"title\":\"motifeR: An Integrated Web Software for Identification and Visualization of Protein Posttranslational Modification Motifs.\",\"citation\":\"Wang S, Cai Y, Cheng J, Li W, Liu Y, Yang H. motifeR: An Integrated Web Software for Identification and Visualization of Protein Posttranslational Modification Motifs. Proteomics 2019, 19:e1900245.\",\"year\":2019,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/31622013\",\"text\":\"motifeR: An Integrated Web Software for Identification and Visualization of Protein Posttranslational Modification Motifs.\"}},{\"title\":\"Comparative analysis of mRNA and protein degradation in prostate tissues indicates high stability of proteins.\",\"citation\":\"Shao W, Guo T, Toussaint NC, Xue P, Wagner U, Li L, Charmpi K, Zhu Y, Wu J, Buljan M, Sun R, Rutishauser D, Hermanns T, Fankhauser CD, Poyet C, Ljubicic J, Rupp N, Rüschoff JH, Zhong Q, Beyer A, Ji J, Collins BC, Liu Y, Rätsch G, Wild PJ, Aebersold R. Comparative analysis of mRNA and protein degradation in prostate tissues indicates high stability of proteins. Nature Communications 2019, 10:2524.\",\"year\":2019,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/31175306\",\"text\":\"Comparative analysis of mRNA and protein degradation in prostate tissues indicates high stability of proteins.\"}},{\"title\":\"Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry.\",\"citation\":\"Bouchal P, Schubert OT, Faktor J, Capkova L, Imrichova H, Zoufalova K, Paralova V, Hrstka R, Liu Y, Ebhardt HA, Budinska E, Nenutil R, Aebersold R. Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry. Cell Reports 2019, 28:832-843.e7.\",\"year\":2019,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/31315058\",\"text\":\"Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry.\"}},{\"title\":\"Capillary zone electrophoresis-tandem mass spectrometry using ultraviolet photodissociation (213 nm) for large-scale top-down proteomics.\",\"citation\":\"McCool EN, Chen D, Li W, Liu Y, Sun L. Capillary zone electrophoresis-tandem mass spectrometry using ultraviolet photodissociation (213 nm) for large-scale top-down proteomics. Analytical Methods : Advancing Methods And Applications 2019, 11:2855-2861.\",\"year\":2019,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/31608127\",\"text\":\"Capillary zone electrophoresis-tandem mass spectrometry using ultraviolet photodissociation (213 nm) for large-scale top-down proteomics.\"}},{\"title\":\"Similarities and Differences of Blood N-Glycoproteins in Five Solid Carcinomas at Localized Clinical Stage Analyzed by SWATH-MS.\",\"citation\":\"Sajic T, Liu Y, Arvaniti E, Surinova S, Williams EG, Schiess R, Hüttenhain R, Sethi A, Pan S, Brentnall TA, Chen R, Blattmann P, Friedrich B, Niméus E, Malander S, Omlin A, Gillessen S, Claassen M, Aebersold R. Similarities and Differences of Blood N-Glycoproteins in Five Solid Carcinomas at Localized Clinical Stage Analyzed by SWATH-MS. Cell Reports 2018, 23:2819-2831.e5.\",\"year\":2018,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/29847809\",\"text\":\"Similarities and Differences of Blood N-Glycoproteins in Five Solid Carcinomas at Localized Clinical Stage Analyzed by SWATH-MS.\"}},{\"title\":\"Proximity-enhanced SuFEx chemical cross-linker for specific and multitargeting cross-linking mass spectrometry.\",\"citation\":\"Yang B, Wu H, Schnier PD, Liu Y, Liu J, Wang N, DeGrado WF, Wang L. Proximity-enhanced SuFEx chemical cross-linker for specific and multitargeting cross-linking mass spectrometry. Proceedings Of The National Academy Of Sciences Of The United States Of America 2018, 115:11162-11167.\",\"year\":2018,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/30322930\",\"text\":\"Proximity-enhanced SuFEx chemical cross-linker for specific and multitargeting cross-linking mass spectrometry.\"}},{\"title\":\"Systems pharmacology using mass spectrometry identifies critical response nodes in prostate cancer.\",\"citation\":\"Ebhardt HA, Root A, Liu Y, Gauthier NP, Sander C, Aebersold R. Systems pharmacology using mass spectrometry identifies critical response nodes in prostate cancer. NPJ Systems Biology And Applications 2018, 4:26.\",\"year\":2018,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/29977602\",\"text\":\"Systems pharmacology using mass spectrometry identifies critical response nodes in prostate cancer.\"}},{\"title\":\"Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS.\",\"citation\":\"Rosenberger G, Liu Y, Röst HL, Ludwig C, Buil A, Bensimon A, Soste M, Spector TD, Dermitzakis ET, Collins BC, Malmström L, Aebersold R. Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS. Nature Biotechnology 2017, 35:781-788.\",\"year\":2017,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/28604659\",\"text\":\"Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS.\"}},{\"title\":\"A Class of Environmental and Endogenous Toxins Induces BRCA2 Haploinsufficiency and Genome Instability.\",\"citation\":\"Tan SLW, Chadha S, Liu Y, Gabasova E, Perera D, Ahmed K, Constantinou S, Renaudin X, Lee M, Aebersold R, Venkitaraman AR. A Class of Environmental and Endogenous Toxins Induces BRCA2 Haploinsufficiency and Genome Instability. Cell 2017, 169:1105-1118.e15.\",\"year\":2017,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/28575672\",\"text\":\"A Class of Environmental and Endogenous Toxins Induces BRCA2 Haploinsufficiency and Genome Instability.\"}},{\"title\":\"Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry.\",\"citation\":\"Collins BC, Hunter CL, Liu Y, Schilling B, Rosenberger G, Bader SL, Chan DW, Gibson BW, Gingras AC, Held JM, Hirayama-Kurogi M, Hou G, Krisp C, Larsen B, Lin L, Liu S, Molloy MP, Moritz RL, Ohtsuki S, Schlapbach R, Selevsek N, Thomas SN, Tzeng SC, Zhang H, Aebersold R. Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry. Nature Communications 2017, 8:291.\",\"year\":2017,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/28827567\",\"text\":\"Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry.\"}},{\"title\":\"Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses.\",\"citation\":\"Rosenberger G, Bludau I, Schmitt U, Heusel M, Hunter CL, Liu Y, MacCoss MJ, MacLean BX, Nesvizhskii AI, Pedrioli PGA, Reiter L, Röst HL, Tate S, Ting YS, Collins BC, Aebersold R. Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses. Nature Methods 2017, 14:921-927.\",\"year\":2017,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/28825704\",\"text\":\"Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses.\"}},{\"title\":\"Shotgun and Targeted Plasma Proteomics to Predict Prognosis of Non-Small Cell Lung Cancer.\",\"citation\":\"Li QR, Liu YS, Zeng R. Shotgun and Targeted Plasma Proteomics to Predict Prognosis of Non-Small Cell Lung Cancer. Methods In Molecular Biology (Clifton, N.J.) 2017, 1619:385-394.\",\"year\":2017,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/28674898\",\"text\":\"Shotgun and Targeted Plasma Proteomics to Predict Prognosis of Non-Small Cell Lung Cancer.\"}},{\"title\":\"Comparison of targeted proteomics approaches for detecting and quantifying proteins derived from human cancer tissues.\",\"citation\":\"Faktor J, Sucha R, Paralova V, Liu Y, Bouchal P. Comparison of targeted proteomics approaches for detecting and quantifying proteins derived from human cancer tissues. Proteomics 2017, 17.\",\"year\":2017,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/27966270\",\"text\":\"Comparison of targeted proteomics approaches for detecting and quantifying proteins derived from human cancer tissues.\"}},{\"title\":\"Protein kinase D at the Golgi controls NLRP3 inflammasome activation.\",\"citation\":\"Zhang Z, Meszaros G, He WT, Xu Y, de Fatima Magliarelli H, Mailly L, Mihlan M, Liu Y, Puig Gámez M, Goginashvili A, Pasquier A, Bielska O, Neven B, Quartier P, Aebersold R, Baumert TF, Georgel P, Han J, Ricci R. Protein kinase D at the Golgi controls NLRP3 inflammasome activation. The Journal Of Experimental Medicine 2017, 214:2671-2693.\",\"year\":2017,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/28716882\",\"text\":\"Protein kinase D at the Golgi controls NLRP3 inflammasome activation.\"}},{\"title\":\"TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics.\",\"citation\":\"Röst HL, Liu Y, D'Agostino G, Zanella M, Navarro P, Rosenberger G, Collins BC, Gillet L, Testa G, Malmström L, Aebersold R. TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics. Nature Methods 2016, 13:777-83.\",\"year\":2016,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/27479329\",\"text\":\"TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics.\"}},{\"title\":\"Quantitative variability of 342 plasma proteins in a human twin population.\",\"citation\":\"Liu Y, Buil A, Collins BC, Gillet LC, Blum LC, Cheng LY, Vitek O, Mouritsen J, Lachance G, Spector TD, Dermitzakis ET, Aebersold R. Quantitative variability of 342 plasma proteins in a human twin population. Molecular Systems Biology 2015, 11:786.\",\"year\":2015,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/25652787\",\"text\":\"Quantitative variability of 342 plasma proteins in a human twin population.\"}},{\"title\":\"Deep Phosphoproteomic Measurements Pinpointing Drug Induced Protective Mechanisms in Neuronal Cells.\",\"citation\":\"Yu C, Gao J, Zhou Y, Chen X, Xiao R, Zheng J, Liu Y, Zhou H. Deep Phosphoproteomic Measurements Pinpointing Drug Induced Protective Mechanisms in Neuronal Cells. Frontiers In Physiology 2016, 7:635.\",\"year\":2016,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/28066266\",\"text\":\"Deep Phosphoproteomic Measurements Pinpointing Drug Induced Protective Mechanisms in Neuronal Cells.\"}},{\"title\":\"The interdependence of transcript and protein abundance: new data--new complexities.\",\"citation\":\"Liu Y, Aebersold R. The interdependence of transcript and protein abundance: new data--new complexities. Molecular Systems Biology 2016, 12:856.\",\"year\":2016,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/26792872\",\"text\":\"The interdependence of transcript and protein abundance: new data--new complexities.\"}},{\"title\":\"Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity.\",\"citation\":\"Zhong Q, Rüschoff JH, Guo T, Gabrani M, Schüffler PJ, Rechsteiner M, Liu Y, Fuchs TJ, Rupp NJ, Fankhauser C, Buhmann JM, Perner S, Poyet C, Blattner M, Soldini D, Moch H, Rubin MA, Noske A, Rüschoff J, Haffner MC, Jochum W, Wild PJ. Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity. Scientific Reports 2016, 6:24146.\",\"year\":2016,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/27052161\",\"text\":\"Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity.\"}},{\"title\":\"Using data-independent, high-resolution mass spectrometry in protein biomarker research: perspectives and clinical applications.\",\"citation\":\"Sajic T, Liu Y, Aebersold R. Using data-independent, high-resolution mass spectrometry in protein biomarker research: perspectives and clinical applications. Proteomics. Clinical Applications 2015, 9:307-21.\",\"year\":2015,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/25504613\",\"text\":\"Using data-independent, high-resolution mass spectrometry in protein biomarker research: perspectives and clinical applications.\"}},{\"title\":\"Prediction of colorectal cancer diagnosis based on circulating plasma proteins.\",\"citation\":\"Surinova S, Choi M, Tao S, Schüffler PJ, Chang CY, Clough T, Vysloužil K, Khoylou M, Srovnal J, Liu Y, Matondo M, Hüttenhain R, Weisser H, Buhmann JM, Hajdúch M, Brenner H, Vitek O, Aebersold R. Prediction of colorectal cancer diagnosis based on circulating plasma proteins. EMBO Molecular Medicine 2015, 7:1166-78.\",\"year\":2015,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/26253081\",\"text\":\"Prediction of colorectal cancer diagnosis based on circulating plasma proteins.\"}},{\"title\":\"Multiplexed Targeted Mass Spectrometry-Based Assays for the Quantification of N-Linked Glycosite-Containing Peptides in Serum.\",\"citation\":\"Thomas SN, Harlan R, Chen J, Aiyetan P, Liu Y, Sokoll LJ, Aebersold R, Chan DW, Zhang H. Multiplexed Targeted Mass Spectrometry-Based Assays for the Quantification of N-Linked Glycosite-Containing Peptides in Serum. Analytical Chemistry 2015, 87:10830-8.\",\"year\":2015,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/26451657\",\"text\":\"Multiplexed Targeted Mass Spectrometry-Based Assays for the Quantification of N-Linked Glycosite-Containing Peptides in Serum.\"}},{\"title\":\"Glycoproteomic analysis of prostate cancer tissues by SWATH mass spectrometry discovers N-acylethanolamine acid amidase and protein tyrosine kinase 7 as signatures for tumor aggressiveness.\",\"citation\":\"Liu Y, Chen J, Sethi A, Li QK, Chen L, Collins B, Gillet LC, Wollscheid B, Zhang H, Aebersold R. Glycoproteomic analysis of prostate cancer tissues by SWATH mass spectrometry discovers N-acylethanolamine acid amidase and protein tyrosine kinase 7 as signatures for tumor aggressiveness. Molecular & Cellular Proteomics : MCP 2014, 13:1753-68.\",\"year\":2014,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/24741114\",\"text\":\"Glycoproteomic analysis of prostate cancer tissues by SWATH mass spectrometry discovers N-acylethanolamine acid amidase and protein tyrosine kinase 7 as signatures for tumor aggressiveness.\"}},{\"title\":\"A repository of assays to quantify 10,000 human proteins by SWATH-MS.\",\"citation\":\"Rosenberger G, Koh CC, Guo T, Röst HL, Kouvonen P, Collins BC, Heusel M, Liu Y, Caron E, Vichalkovski A, Faini M, Schubert OT, Faridi P, Ebhardt HA, Matondo M, Lam H, Bader SL, Campbell DS, Deutsch EW, Moritz RL, Tate S, Aebersold R. A repository of assays to quantify 10,000 human proteins by SWATH-MS. Scientific Data 2014, 1:140031.\",\"year\":2014,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/25977788\",\"text\":\"A repository of assays to quantify 10,000 human proteins by SWATH-MS.\"}},{\"title\":\"Cardioprotective effects of oxymatrine on isoproterenol-induced heart failure via regulation of DDAH/ADMA metabolism pathway in rats.\",\"citation\":\"Zhang W, Zhang J, Liu YK, Liu J, Wang X, Xu Q, Wang Y, Xu X, Dai G. Cardioprotective effects of oxymatrine on isoproterenol-induced heart failure via regulation of DDAH/ADMA metabolism pathway in rats. European Journal Of Pharmacology 2014, 745:29-35.\",\"year\":2014,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/25310909\",\"text\":\"Cardioprotective effects of oxymatrine on isoproterenol-induced heart failure via regulation of DDAH/ADMA metabolism pathway in rats.\"}},{\"title\":\"Quantitative measurements of N-linked glycoproteins in human plasma by SWATH-MS.\",\"citation\":\"Liu Y, Hüttenhain R, Surinova S, Gillet LC, Mouritsen J, Brunner R, Navarro P, Aebersold R. Quantitative measurements of N-linked glycoproteins in human plasma by SWATH-MS. Proteomics 2013, 13:1247-56.\",\"year\":2013,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/23322582\",\"text\":\"Quantitative measurements of N-linked glycoproteins in human plasma by SWATH-MS.\"}},{\"title\":\"Mass spectrometric protein maps for biomarker discovery and clinical research.\",\"citation\":\"Liu Y, Hüttenhain R, Collins B, Aebersold R. Mass spectrometric protein maps for biomarker discovery and clinical research. Expert Review Of Molecular Diagnostics 2013, 13:811-25.\",\"year\":2013,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/24138574\",\"text\":\"Mass spectrometric protein maps for biomarker discovery and clinical research.\"}},{\"title\":\"Integrative proteomics and tissue microarray profiling indicate the association between overexpressed serum proteins and non-small cell lung cancer.\",\"citation\":\"Liu Y, Luo X, Hu H, Wang R, Sun Y, Zeng R, Chen H. Integrative proteomics and tissue microarray profiling indicate the association between overexpressed serum proteins and non-small cell lung cancer. PloS One 2012, 7:e51748.\",\"year\":2012,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/23284758\",\"text\":\"Integrative proteomics and tissue microarray profiling indicate the association between overexpressed serum proteins and non-small cell lung cancer.\"}},{\"title\":\"Quantitative proteomics reveal up-regulated protein expression of the SET complex associated with hepatocellular carcinoma.\",\"citation\":\"Li C, Ruan HQ, Liu YS, Xu MJ, Dai J, Sheng QH, Tan YX, Yao ZZ, Wang HY, Wu JR, Zeng R. Quantitative proteomics reveal up-regulated protein expression of the SET complex associated with hepatocellular carcinoma. Journal Of Proteome Research 2012, 11:871-85.\",\"year\":2012,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/22082227\",\"text\":\"Quantitative proteomics reveal up-regulated protein expression of the SET complex associated with hepatocellular carcinoma.\"}},{\"title\":\"Shotgun and targeted proteomics reveal that pre-surgery serum levels of LRG1, SAA, and C4BP may refine prognosis of resected squamous cell lung cancer.\",\"citation\":\"Liu YS, Luo XY, Li QR, Li H, Li C, Ni H, Li RX, Wang R, Hu HC, Pan YJ, Chen HQ, Zeng R. Shotgun and targeted proteomics reveal that pre-surgery serum levels of LRG1, SAA, and C4BP may refine prognosis of resected squamous cell lung cancer. Journal Of Molecular Cell Biology 2012, 4:344-7.\",\"year\":2012,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/23042802\",\"text\":\"Shotgun and targeted proteomics reveal that pre-surgery serum levels of LRG1, SAA, and C4BP may refine prognosis of resected squamous cell lung cancer.\"}},{\"title\":\"Proteomic mining in the dysplastic liver of WHV/c-myc mice--insights and indicators for early hepatocarcinogenesis.\",\"citation\":\"Liu Y, Li C, Xing Z, Yuan X, Wu Y, Xu M, Tu K, Li Q, Wu C, Zhao M, Zeng R. Proteomic mining in the dysplastic liver of WHV/c-myc mice--insights and indicators for early hepatocarcinogenesis. The FEBS Journal 2010, 277:4039-53.\",\"year\":2010,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/20807235\",\"text\":\"Proteomic mining in the dysplastic liver of WHV/c-myc mice--insights and indicators for early hepatocarcinogenesis.\"}},{\"title\":\"A high-quality secretome of A549 cells aided the discovery of C4b-binding protein as a novel serum biomarker for non-small cell lung cancer.\",\"citation\":\"Luo X, Liu Y, Wang R, Hu H, Zeng R, Chen H. A high-quality secretome of A549 cells aided the discovery of C4b-binding protein as a novel serum biomarker for non-small cell lung cancer. Journal Of Proteomics 2011, 74:528-38.\",\"year\":2011,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/21262398\",\"text\":\"A high-quality secretome of A549 cells aided the discovery of C4b-binding protein as a novel serum biomarker for non-small cell lung cancer.\"}},{\"title\":\"Speeding up tandem mass spectrometry based database searching by peptide and spectrum indexing.\",\"citation\":\"Li Y, Chi H, Wang LH, Wang HP, Fu Y, Yuan ZF, Li SJ, Liu YS, Sun RX, Zeng R, He SM. Speeding up tandem mass spectrometry based database searching by peptide and spectrum indexing. Rapid Communications In Mass Spectrometry : RCM 2010, 24:807-14.\",\"year\":2010,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/20187083\",\"text\":\"Speeding up tandem mass spectrometry based database searching by peptide and spectrum indexing.\"}},{\"title\":\"Selection of Features with Consistent Profiles Improves Relative Protein Quantification in Mass Spectrometry Experiments.\",\"citation\":\"Tsai TH, Choi M, Banfai B, Liu Y, MacLean B, Dunkley T, Vitek O. Selection of Features with Consistent Profiles Improves Relative Protein Quantification in Mass Spectrometry Experiments. Molecular & Cellular Proteomics : MCP 2020, 19:944-959.\",\"year\":2020,\"link\":{\"url\":\"https://www.ncbi.nlm.nih.gov/pubmed/32234965\",\"text\":\"Selection of Features with Consistent Profiles Improves Relative Protein Quantification in Mass Spectrometry Experiments.\"}}],\"clinicalTrials\":[],\"coauthors\":[]},\"patientCareTab\":null,\"newsTab\":{\"searchUrl\":null,\"news\":[{\"id\":\"19487\",\"bylineDate\":\"2019-02-18T05:00:00-05:00\",\"title\":\"Study Finds Wide Variation Among Human Cell Lines Used for Research\",\"summary\":\"One reason why an estimated 70% of researchers cannot reproduce other scientists' experiments may lie in significant differences in cell lines used by different laboratories, according to Yale researcher Yansheng Liu.\",\"thumbnail\":{\"url\":\"https://ysm-res.cloudinary.com/image/upload/v1/yms/prod/a8ae7914-c00a-4151-a39b-ba85d16cc3d8\",\"altText\":null,\"width\":4000,\"height\":2667,\"imageVariants\":[{\"dimension\":\"Square\",\"url\":\"https://ysm-res.cloudinary.com/image/upload/v1/yms/prod/711d03de-65c6-4881-aa6f-6115c99b8862\",\"width\":2667,\"height\":2667},{\"dimension\":\"Rectangle\",\"url\":\"https://ysm-res.cloudinary.com/image/upload/v1/yms/prod/143e0318-a8c4-4dd2-9438-484bdb336874\",\"width\":2681,\"height\":1839}]},\"url\":\"/bbs/molmed/news-article/19487/\",\"isFeatured\":false,\"source\":null},{\"id\":\"19368\",\"bylineDate\":\"2019-01-17T05:00:00-05:00\",\"title\":\"Mass Spectrometry and Proteomics: Powerful Tools for Cancer Research\",\"summary\":\"Advances in mass spectrometry and proteomics are giving researchers new ways to better understand, detect, diagnose, and treat cancer.\",\"thumbnail\":{\"url\":\"https://ysm-res.cloudinary.com/image/upload/v1/yms/prod/db77f32b-ac87-48c6-ab24-7361b363c956\",\"altText\":null,\"width\":1600,\"height\":933,\"imageVariants\":[{\"dimension\":\"Square\",\"url\":\"https://ysm-res.cloudinary.com/image/upload/v1/yms/prod/05ca0657-9dd3-43ff-a32f-3867a8075a1b\",\"width\":933,\"height\":933},{\"dimension\":\"Rectangle\",\"url\":\"https://ysm-res.cloudinary.com/image/upload/v1/yms/prod/5d397ad5-bfe1-4623-98b6-aa59fc1bbecc\",\"width\":1359,\"height\":933}]},\"url\":\"/bbs/molmed/news-article/19368/\",\"isFeatured\":false,\"source\":null}]},\"locationsTab\":{\"addresses\":[{\"id\":23648,\"address\":{\"id\":664,\"officeName\":\"Liu lab\",\"name\":\"West Campus Advanced Biosciences Center\",\"addressLine1\":\"840 West Campus Drive\",\"addressLine2\":\"Fl 3rd, Ste Cancer Biology Institute, Rm 371A\",\"city\":\"West Haven\",\"region\":\"CT\",\"country\":\"United States\",\"postalCode\":\"06516\"},\"geoPoint\":{\"latitude\":41.2569183,\"longitude\":-72.9896989},\"phones\":[],\"activeHours\":null,\"website\":null}]},\"metaData\":{\"title\":\"Yansheng Liu, PhD\",\"description\":\"Dr. Liu received his PhD of Biomedical Sciences at Shanghai Institute for Biological Sciences, Chinese Academy of Sciences. 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Systematic proteome and proteostasis profiling in human Trisomy 21 fibroblast cells. Nature Communications 2017, 8:1212.\\\",\\\"@context\\\":\\\"http://schema.org\\\"}\"},{\"schemaName\":\"MedicalScholarlyArticle\",\"jsonData\":\"{\\\"@type\\\":\\\"MedicalScholarlyArticle\\\",\\\"publicationType\\\":\\\"Journal Article\\\",\\\"inLanguage\\\":\\\"en-US\\\",\\\"headline\\\":\\\"On the Dependency of Cellular Protein Levels on mRNA Abundance.\\\",\\\"url\\\":\\\"https://www.ncbi.nlm.nih.gov/pubmed/27104977\\\",\\\"author\\\":[{\\\"@type\\\":\\\"Person\\\",\\\"mainEntityOfPage\\\":{\\\"@type\\\":\\\"WebPage\\\",\\\"@id\\\":\\\"https://medicine.yale.edu/ysm/profile/yansheng_liu/\\\",\\\"@context\\\":\\\"http://schema.org\\\"},\\\"name\\\":\\\"Yansheng Liu\\\",\\\"description\\\":\\\"Dr. Liu received his PhD of Biomedical Sciences at Shanghai Institute for Biological Sciences, Chinese Academy of Sciences. 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Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS. Nature Biotechnology 2017, 35:781-788.\\\",\\\"@context\\\":\\\"http://schema.org\\\"}\"},{\"schemaName\":\"MedicalScholarlyArticle\",\"jsonData\":\"{\\\"@type\\\":\\\"MedicalScholarlyArticle\\\",\\\"publicationType\\\":\\\"Journal Article\\\",\\\"inLanguage\\\":\\\"en-US\\\",\\\"headline\\\":\\\"A Class of Environmental and Endogenous Toxins Induces BRCA2 Haploinsufficiency and Genome Instability.\\\",\\\"url\\\":\\\"https://www.ncbi.nlm.nih.gov/pubmed/28575672\\\",\\\"author\\\":[{\\\"@type\\\":\\\"Person\\\",\\\"mainEntityOfPage\\\":{\\\"@type\\\":\\\"WebPage\\\",\\\"@id\\\":\\\"https://medicine.yale.edu/ysm/profile/yansheng_liu/\\\",\\\"@context\\\":\\\"http://schema.org\\\"},\\\"name\\\":\\\"Yansheng Liu\\\",\\\"description\\\":\\\"Dr. Liu received his PhD of Biomedical Sciences at Shanghai Institute for Biological Sciences, Chinese Academy of Sciences. 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A Class of Environmental and Endogenous Toxins Induces BRCA2 Haploinsufficiency and Genome Instability. Cell 2017, 169:1105-1118.e15.\\\",\\\"@context\\\":\\\"http://schema.org\\\"}\"},{\"schemaName\":\"MedicalScholarlyArticle\",\"jsonData\":\"{\\\"@type\\\":\\\"MedicalScholarlyArticle\\\",\\\"publicationType\\\":\\\"Journal Article\\\",\\\"inLanguage\\\":\\\"en-US\\\",\\\"headline\\\":\\\"Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectro\\\",\\\"url\\\":\\\"https://www.ncbi.nlm.nih.gov/pubmed/28827567\\\",\\\"author\\\":[{\\\"@type\\\":\\\"Person\\\",\\\"mainEntityOfPage\\\":{\\\"@type\\\":\\\"WebPage\\\",\\\"@id\\\":\\\"https://medicine.yale.edu/ysm/profile/yansheng_liu/\\\",\\\"@context\\\":\\\"http://schema.org\\\"},\\\"name\\\":\\\"Yansheng Liu\\\",\\\"description\\\":\\\"Dr. Liu received his PhD of Biomedical Sciences at Shanghai Institute for Biological Sciences, Chinese Academy of Sciences. 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Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry. Nature Communications 2017, 8:291.\\\",\\\"@context\\\":\\\"http://schema.org\\\"}\"},{\"schemaName\":\"MedicalScholarlyArticle\",\"jsonData\":\"{\\\"@type\\\":\\\"MedicalScholarlyArticle\\\",\\\"publicationType\\\":\\\"Journal Article\\\",\\\"inLanguage\\\":\\\"en-US\\\",\\\"headline\\\":\\\"Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition an\\\",\\\"url\\\":\\\"https://www.ncbi.nlm.nih.gov/pubmed/28825704\\\",\\\"author\\\":[{\\\"@type\\\":\\\"Person\\\",\\\"mainEntityOfPage\\\":{\\\"@type\\\":\\\"WebPage\\\",\\\"@id\\\":\\\"https://medicine.yale.edu/ysm/profile/yansheng_liu/\\\",\\\"@context\\\":\\\"http://schema.org\\\"},\\\"name\\\":\\\"Yansheng Liu\\\",\\\"description\\\":\\\"Dr. Liu received his PhD of Biomedical Sciences at Shanghai Institute for Biological Sciences, Chinese Academy of Sciences. 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Comparison of targeted proteomics approaches for detecting and quantifying proteins derived from human cancer tissues. Proteomics 2017, 17.\\\",\\\"@context\\\":\\\"http://schema.org\\\"}\"},{\"schemaName\":\"MedicalScholarlyArticle\",\"jsonData\":\"{\\\"@type\\\":\\\"MedicalScholarlyArticle\\\",\\\"publicationType\\\":\\\"Journal Article\\\",\\\"inLanguage\\\":\\\"en-US\\\",\\\"headline\\\":\\\"Protein kinase D at the Golgi controls NLRP3 inflammasome activation.\\\",\\\"url\\\":\\\"https://www.ncbi.nlm.nih.gov/pubmed/28716882\\\",\\\"author\\\":[{\\\"@type\\\":\\\"Person\\\",\\\"mainEntityOfPage\\\":{\\\"@type\\\":\\\"WebPage\\\",\\\"@id\\\":\\\"https://medicine.yale.edu/ysm/profile/yansheng_liu/\\\",\\\"@context\\\":\\\"http://schema.org\\\"},\\\"name\\\":\\\"Yansheng Liu\\\",\\\"description\\\":\\\"Dr. Liu received his PhD of Biomedical Sciences at Shanghai Institute for Biological Sciences, Chinese Academy of Sciences. 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Glycoproteomic analysis of prostate cancer tissues by SWATH mass spectrometry discovers N-acylethanolamine acid amidase and protein tyrosine kinase 7 as signatures for tumor aggressiveness. 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Integrative proteomics and tissue microarray profiling indicate the association between overexpressed serum proteins and non-small cell lung cancer. 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Shotgun and targeted proteomics reveal that pre-surgery serum levels of LRG1, SAA, and C4BP may refine prognosis of resected squamous cell lung cancer. 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