Published in Biotechnology Journal, 2012
Reviewed challenges in integrating heterogeneous datasets to derive robust molecular biomarkers for diseases, and recommended best practices
Recommended citation: Sung J, Wang Y, Chandrasekaran S, Witten DM, Price ND: Molecular signatures from omics data: From chaos to consensus. Biotechnology journal. 7:946-957, 2012 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3418428/
Published in BMC Systems Biology, 2012
Developed the mCADRE algorithm, which leverages network topology to achieve 1000 fold speed up while achieving similar and higher accuracy
Recommended citation: Wang Y, Eddy JA, Price ND: Reconstruction of genome-scale metabolic models for 126 human tissues using mCADRE. BMC Syst Biol. 6:153-153, 2012 https://bmcsystbiol.biomedcentral.com/articles/10.1186/1752-0509-6-153
Published in Nature Cell Biology, 2015
Integrated trancriptomic, epigenomic, and metabolomic data and discovered that NNMT, a metabolic enzyme, regulates H3K27me3 methylation levels in naive to primed transition.
Recommended citation: Sperber H, Mathieu J, Wang Y, Ferreccio A, Hesson J, Xu Z, Fischer KA, Devi A, Detraux D, Gu H, Battle SL, Showalter M, Valensisi C, Bielas JH, Ericson NG, Margaretha L, Robitaille AM, Margineantu D, Fiehn O, Hockenbery D, Blau CA, Raftery D, Margolin AA, Hawkins RD, Moon RT, Ware CB, Ruohola-Baker H: The metabolome regulates the epigenetic landscape during naive-to-primed human embryonic stem cell transition. Nat Cell Biol. 17:1523-1535, 2015 https://www.nature.com/articles/ncb3264
Published in Seminars in cell & developmental biology, 2016
Review literature on metabolic changes in cardiomyocyte maturation
Recommended citation: Ellen Kreipke R, Wang Y, Miklas JW, Mathieu J, Ruohola-Baker H: Metabolic remodeling in early development and cardiomyocyte maturation. Semin Cell Dev Biol. 52:84-92, 2016 https://www.sciencedirect.com/science/article/pii/S1084952116300489
Published in PNAS, 2017
Integrated RNA-seq, proteomic and metabolomic datasets to identify molecular signatures of positional memory in zebrafish fin regeneration
Recommended citation: Rabinowitz JS, Robitaille AM, Wang Y, Ray CA, Thummel R, Gu H, Djukovic D, Raftery D, Berndt JD, Moon RT: Transcriptomic, proteomic, and metabolomic landscape of positional memory in the caudal fin of zebrafish. Proc Natl Acad Sci U S A. 114:E717-E726, 2017 https://www.pnas.org/content/114/5/E717.short
Published in Cell Reports, 2017
Developed an algorithm to identify regulatory genes that exhibit consistent changes in mRNA level and histone methylation levels.
Recommended citation: Palpant NJ, Wang Y, Hadland B, Zaunbrecher RJ, Redd M, Jones D, Pabon L, Jain R, Epstein J, Ruzzo WL, Zheng Y, Bernstein I, Margolin A, Murry CE: Chromatin and transcriptional analysis of mesoderm progenitor cells identifies HOPX as a regulator of primitive hematopoiesis. Cell Rep. 20:1597-1608, 2017 https://www.sciencedirect.com/science/article/pii/S2211124717310604
Published in PNAS, 2018
Integrated RNA-seq and ChIP-seq of histone marks to find genes regulated by LSD1
Recommended citation: Sehrawat A, Gao L, Wang Y, Bankhead A, McWeeney SK, King CJ, Schwartzman J, Urrutia J, Bisson WH, Coleman DJ, Joshi SK, Kim DH, Sampson DA, Weinmann S, Kallakury BVS, Berry DL, Haque R, Van Den Eeden, S K, Sharma S, Bearss J, Beer TM, Thomas GV, Heiser LM, Alumkal JJ: LSD1 activates a lethal prostate cancer gene network independently of its demethylase function. Proc Natl Acad Sci U S A. 115:E4179-E4188, 2018 https://www.pnas.org/content/115/18/E4179.short
Published in Aging, 2018
Uncovered dramatic sex-specific differences in the aging process of cells of the renin lineage (progenitors for kidney podocytes).
Recommended citation: Wang Y, Eng DG, Pippin JW, Gharib SA, McClelland A, Gross KW, Shankland SJ: Sex differences in transcriptomic profiles in aged kidney cells of renin lineage. Aging (Albany NY). 10:606-621, 2018 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5940125/
Published in Kidney International, 2018
Perspective on a study that identified DNA methylation markers of kidney funciton in diabetic kidney disease
Recommended citation: Bomsztyk K, Denisenko O, Wang Y: DNA methylation yields epigenetic clues into the diabetic nephropathy of pima indians. Kidney Int. 93:1272-1275, 2018 https://www.sciencedirect.com/science/article/pii/S0085253818301972
Published in Advanced Science, 2019
RNA-seq of engineered vasculature with different conditions
Recommended citation: Nagao RJ, Marcu R, Wang Y, Wang L, Arakawa C, DeForest C, Chen J, Lopez JA, Zheng Y: Transforming endothelium with platelet-rich plasma in engineered microvessels. Adv Sci (Weinh). 6:1901725, 2019 https://onlinelibrary.wiley.com/doi/abs/10.1002/advs.201901725
Published in Nature Communications, 2019
Integrating RNA-seq, ChIP-seq and CRISPR screens to identify regulators of naive to primed transition
Recommended citation: Mathieu J, Detraux D, Kuppers D, Wang Y, Cavanaugh C, Sidhu S, Levy S, Robitaille AM, Ferreccio A, Bottorff T, McAlister A, Somasundaram L, Artoni F, Battle S, Hawkins RD, Moon RT, Ware CB, Paddison PJ, Ruohola-Baker H: Folliculin regulates mTORC1/2 and WNT pathways in early human pluripotency. Nature communications. 10:632, 2019 https://www.nature.com/articles/s41467-018-08020-0
Published in Nucleic Acids Research, 2019
Evaluate latest the high sample throughput, low cost PIXUL-ChIP against traditional ChIP-seq
Recommended citation: Bomsztyk K, Mar D, Wang Y, Denisenko O, Ware C, Frazar CD, Blattler A, Maxwell AD, MacConaghy BE, Matula TJ: PIXUL-ChIP: Integrated high-throughput sample preparation and analytical platform for epigenetic studies. Nucleic Acids Res. 47:e69, 2019 https://academic.oup.com/nar/article-abstract/47/12/e69/5423606
Published in Epigenomics, 2019
Review literature and propose approaches to target epigenetic abberations in cancer
Recommended citation: Bomsztyk K, Wang Y: Genome-bound enzymes as epigenetic drug targets in cancer. Epigenomics. 11:1463-1467, 2019 https://www.futuremedicine.com/doi/abs/10.2217/epi-2019-0197
Published in Stem Cell Reports, 2019
Use RNA-seq to assess the effects of fatty acid on the maturation of hPSC-CM
Recommended citation: Yang X, Rodriguez ML, Leonard A, Sun L, Fischer KA, Wang Y, Ritterhoff J, Zhao L, Kolwicz SC, Pabon L, Reinecke H, Sniadecki NJ, Tian R, Ruohola-Baker H, Xu H, Murry CE: Fatty acids enhance the maturation of cardiomyocytes derived from human pluripotent stem cells. Stem Cell Reports. 13:657-668, 2019 https://www.sciencedirect.com/science/article/pii/S2213671119303078
Published in Nature Communications, 2019
scRNA-seq to discover molecular signatures of hPSC-CM maturation
Recommended citation: Miklas JW, Clark E, Levy S, Detraux D, Leonard A, Beussman K, Showalter MR, Smith AT, Hofsteen P, Yang X, Macadangdang J, Manninen T, Raftery D, Madan A, Suomalainen A, Kim DH, Murry CE, Fiehn O, Sniadecki NJ, Wang Y, Ruohola-Baker H: TFPa/HADHA is required for fatty acid beta-oxidation and cardiolipin re-modeling in human cardiomyocytes. Nat Commun. 10:4671-1, 2019 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6789043/
Published in International Journal of Molecular Sciences, 2019
Integrating multiple mRNA-seq and microRNA-seq datasets to discover important microRNAs regulating pluripotency state transitions
Recommended citation: Wang Y, Hussein AM, Somasundaram L, Sankar R, Detraux D, Mathieu J, Ruohola-Baker H: microRNAs regulating human and mouse naive pluripotency. Int J Mol Sci. 20:10.3390/ijms20235864, 2019 https://www.mdpi.com/1422-0067/20/23/5864
Published in Developmental Cell, 2020
Integrating transcriptomics and metabolomics to study diapause
Recommended citation: Hussein AM, Wang Y, Mathieu J, et al. Metabolic Control over mTOR-Dependent Diapause-like State. Dev Cell. 2020;52(2):236-250 https://www.sciencedirect.com/science/article/abs/pii/S1534580719310676
Published in Biorxiv, 2020
Hear the whispers in scRNA-seq
Recommended citation: Yuliang Wang, talklr uncovers ligand-receptor mediated intercellular crosstalk, bioRxiv 2020.02.01.930602 https://www.biorxiv.org/content/10.1101/2020.02.01.930602v1.abstract
Published in Scientific Reports, 2020
Spatially resolved metabolic networks
Recommended citation: Wang, Y., Ma, S. & Ruzzo, W.L. Spatial modeling of prostate cancer metabolic gene expression reveals extensive heterogeneity and selective vulnerabilities. Sci Rep 10, 3490 (2020). https://www.nature.com/articles/s41598-020-60384-w