​   Publications


Alternative splicing redefines landscape of commonly mutated genes in acute myeloid leukemia

Rivera, O.D., Mallory, M.J., Quesnel-Vallières, M., Chatrikhi, R., Schultz, D.C., Carroll, M., Barash, Y., Cherry, S., Lynch, K.W.

Proc Natl Acad Sci USA 118, e2014967118

CYP11B1 Variants Influence Skeletal Maturation Via Alternative Splicing

Grgic O.*, Gazzara R. M.* et al

Nature Comm. Bio. in press


Disrupting upstream translation in mRNAs is associated with human disease

Lee, D.S.M., Park, J., Kromer, A., Baras, A., Rader, D.J., Ritchie, M.D., Ghanem, L.R., Barash, Y

Nature Comm. 12, 1515

The Global Protein-RNA Interaction map of Epithelial Splicing Regulatory Protein 1 defines a post-transcriptional program that is essential for epithelial cell function

Peart, N.J., Hwang, J.Y., Vallières, M.Q.-, Sears, M.J., Yang, Y., Stoilov, P., Barash, Y., Park, J.W., Carstens, R.P


MOCCASIN: A method for correcting for known and unknown confounders in RNA splicing analysis

Slaff, B., Radens, C.M., Jewell, P., Jha, A., Lahens, N.F., Grant, G.R., Thomas-Tikhonenko, A., Lynch, K.W., Barash, Y.

Nature Comm. in press


Mapping RNA splicing variations in clinically accessible and nonaccessible tissues to facilitate Mendelian disease diagnosis using RNA-seq.

Aicher J.K , Jewell P., Vaquero-Garcia J., Barash Y., and Bhoj E.J

Genet Med (2020)

Genomic profiling of human vascular cells identifies TWIST1 as a causal gene for common vascular diseases

Nurnberg ST, Guerraty MA, Rao HS, Pjanic M, Norton S, Serrano F, Perisic L, Elwyn S, Pluta J, Zhao W, Testa S, Park Y, Wang T, Hedin U, Sinha S, Barash Y, Brown CD, Quertermous T, and Rader DJ.

PLoS Genet 16(1): e1008538.

Alternative splicing redefines landscape of commonly mutated genes in acute myeloid leukemia

Rivera O.D, Mallory M.J., Quesnel-Vallières M., Schultz D.C., Carroll M., Barash Y.*, Cherry S*, Lynch K. W.*


Rapid and scalable profiling of nascent RNA with fastGRO

Barbieri E., Hill C., Quesnel-Vallieres M., Barash Y., Gardini A.


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Integrative analysis reveals RNA G-quadruplexes in UTRs are selectively constrained and enriched for functional associations.

Lee, D.S.M., Ghanem, L.R. & Barash, Y.

Nature Com. 11, 527 (2020).

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Enhanced Integrated Gradients: improving interpretability of deep learning models using splicing codes as a case study

Jha A., Aicher J.K, Singh D. and Barash Y.

Genome Biology, 21, 149 (2020)

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Meta-Analysis of Transcriptomic Variation in T cell Populations Reveals Novel Signatures of Gene Expression and Splicing

Radens C.M, Blake D., Jewell P., Barash Y.* and Lynch K.W.*

RNA 10.1261 2020

MOCCASIN: A method for correcting for known and unknown confounders in RNA splicing analysis

Slaff B.*, Radens C.M*, Jewell P., Jha A., Lahens N.F, Grant G.R., Thomas-Tikhonenko A., Lynch K.W., Barash Y.


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An ancient germ cell-specific RNA binding protein protects the germline from cryptic splice site poisoning

Ehrmann I., Crichton J.H., Gazzara M.R. 3,4, James K., Liu Y., Grellscheid S., Curk T., de Rooij D.G., Steyn J., Cockell S.J., Adams I.R, Barash Y. and Elliott D.J

ELife, 2019;8:e39304

URLGoogle Scholar | URL

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Retention of CD19 intron 2 contributes to CART-19 resistance in leukemias with subclonal frameshift mutations in CD19

Asnani, M., Hayer, K.E., Naqvi, A.S. et al.

Leukemia (2019)

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RNA-binding protein A1CF modulates plasma triglyceride levels through posttranscriptional regulation of stress-induced VLDL secretion

Lin, J., Conlon, D.M., Wang, X., Nostrand, E.V., Robano, I., Park, Y., Strong, A., Radmanesh, B., Barash, Y., Rader, D.J., Yeo, W. Y, Musunuru K.


Aberrant splicing in B-cell acute lymphoblastic leukemia

Black, K.L., Naqvi, A.S., Hayer, K.E., Yang, S.Y., Gillespie, E., Bagashev, A., Pillai, V., Tasian, S., Gazzara, M.R., Carroll, M., Taylor D., Lynch K. W., Barash Y., Thomas-Tikhonenko A.

Nucleic Acids Res 46, 11357–11369

Poly(C)-Binding Protein Pcbp2 Enables Differentiation of Definitive Erythropoiesis by Directing Functional Splicing of the Runx1 Transcript

Ghanem LR, Kromer A, Silverman IM, Ji X, Gazzara M, Nguyen N, Aguilar G, Martinelli M, Barash Y, Liebhaber SA.

Mol Cell Biol. 2018 Jul 30;38(16).

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LeafCutter vs. MAJIQ and comparing software in the fast-moving field of genomics

Vaquero-Garcia J., Norton S , Barash Y.

Google Scholar | BioRxiv

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Integrative Deep Models for Alternative Splicing

Jha A., Gazzara M., Barash Y.

Bioinformatics, 33 (14): i274-i282 (selected for ISMB2017 proceedings)

Ancient antagonism between CELF and RBFOX families tunes mRNA splicing outcomes

Gazzara, M., Mallory M., Roytenberg R., Lindberg J., Jha A., Lynch K.*, Barash Y.*

Genome Research, 10.1101/gr.220517.117

PRiMeUM: a model for predicting risk of metastasis in Uveal Melanoma

Vaquero-Garcia J., Lalonde E., Ewens K.G, Ebrahimzadeh J., Richard-Yutz J., Shields C.L., Barrera A., Green C.J. Barash Y.*, Ganguly A.*

Investigative Ophthalmology & Visual Science, Vol.58, p4096-4105. 2017

ESRP1 mutations cause hearing loss due to defects in alternative splicing that disrupt cochlear development

Rohacek A.M., Bebee T.W., Tilton R.K., Radens C.M., McDermott-Roe C., Peart N., Kaur M., Zaykaner M., Cieply B., Musunuru K., Barash Y., Germille J.A., Krantz I.D., Carstens R.P., Epstein D.J.

Developmental Cell, accepted

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MAJIQ-SPEL: Web-tool to interrogate classical and complex splicing variations from RNA-Seq data

Green CJ, Gazzara M.R., Barash Y.

Bioinformatics, doi/10.1093

Outlier detection for improved differential splicing quantification from RNA-Seq experiments with replicates

Norton S., Vaquero-Garcia J., Barash Y.


Phosphoproteomics reveals that glycogen synthase kinase-3 phosphorylates multiple splicing factors and is associated with alternative splicing

Shinde M. Y., Sidoli S., Kulej K., Mallory M.J., Radens C.M., Reicherter A., Myers R., Barash Y., Lynch K.W., Garcia B.A., Klein P.S.

JBC, in press

Transcriptome analysis of hypoxic cancer cells uncovers intron retention in EIF2B5 as a mechanism to inhibit translation

Brady L.K., Wang H., Radens C.M., Bi Y., Radovich M., Maity A., Ivan C., Ivan M., Barash Y., Koumenis C.

Plos Biology, in press

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A new view of transcriptome complexity and regulation through the lens of local splicing variations

Vaquero-Garcia J., Barrera A., Gazzara, M. González-Vallinas J., Lahens N., Hogenesch J., Lynch K., Barash Y.

ELife 2016;10.7554/eLife.11752

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A SLM2 feedback pathway controls cortical network activity and mouse behavior

Ingrid Ehrmann, Matthew R. Gazzara, Vittoria Pagliarini, Caroline Dalgliesh, Mahsa Kheirollahi-Chadegani, Yaobo Xu, Eleonora Cesari, Marina Danilenko, Marie Maclennan, Kate Lowdon, Tanja Vogel, Piia Keskivali-Bond, Sara Wells, Heather Cater, Philippe Fort, Mauro Santibanez-Koref, Silvia Middei, Claudio Sette, Gavin J. Clowry*, Yoseph Barash*, Mark O. Cunningham*, David J. Elliott*

Cell Reports, Volume 17, Issue 12

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Convergence of acquired mutations and alternative splicing of CD19 enables resistance to CART-19 immunotherapy

Sotillo E., Barrett D., Black K., Bagashev A., Oldridge D., Wu G., Sussman R., Lanauze C., Gazzara M, Martinez N., Ruella M., Harrington C., Chung E., Perazzelli J., Hofmann T., Maude S., Raman P., Barrera A., Gill S., Lacey S., Melenhorst J., Allman D., Jacoby E., Fry T., Mackall C., Barash Y., Lynch K., Maris J, Grupp S.,Thomas-Tikhonenko A.

Cancer Discovery, In press

Hui Y. Xiong, Babak Alipanahi, Leo J. Lee, Hannes Bretschneider, Daniele Merico, Ryan K. C. Yuen, Yimin Hua, Serge Gueroussov, Hamed S. Najafabadi, Timothy R. Hughes, Quaid Morris, Yoseph Barash, Adrian R. Krainer, Nebojsa Jojic, Stephen W. Scherer, Benjamin J. Blencowe, Brendan J. Frey

Science. Vol. 347 no. 6218

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Widespread JNK-dependent alternative splicing induces a positive feedback loop through CELF2-mediated regulation of MKK7 during T-cell activation

Martinez N, Agosto L., Qiu J., Mallory M., Gazarra M., Barash Y., Fu X., Lynch K.

Genes & Development Vol. 29 Issue 19

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In silico to in vivo splicing analysis using splicing code models

Gazzara, M., Vaquero-Garcia, J., Lynch, K., Barash, Y.


Splicing Code Modeling

Barash Y. Vaquero-Garcia J.

Systems Biology of RNA Binding Proteins, Editor Yeo G. W., Springer

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Predicting alternative splicing

Barash Y., Vaquero-Garcia J.

Spliceosomal Pre-mRNA Splicing, Hertel K. J. Editor, Springer

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ESRP1 mutations cause hearing loss due to defects in alternative splicing that disrupt cochlear development

Rohacek A.M., Bebee T.W., Tilton R.K., Radens C.M., McDermott-Roe C., Peart N., Kaur M., Zaykaner M., Cieply B., Musunuru K., Barash Y., Germille J.A., Krantz I.D., Carstens R.P., Epstein D.J.

Developmental Cell, accepted

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Bayesian prediction of

tissue-regulated splicing using RNA sequence and cellular context

Xiong H.Y., Barash Y., Frey B.J.

Bioinformatics. 27:2554–2562


An illuminated view of molecular biology

Barash Y., Wang X.

Genome Biology. 11:307

Deciphering the splicing code

Barash Y., Calarco J.A., Gao W., Pan Q., Wang X., Shai O., Blencowe B.J. Frey B.J.

Nature. 465:53–9

Model-based detection of

alternative splicing signals

Barash Y., Blencowe B.J., Frey B.J.


Bioinformatics. 26:i325–i333


A systematic analysis of intronic sequences downstream of 5' splice sites reveals a widespread role for U-rich motifs and TIA1/TIAL1 proteins in alternative

Aznarez I., Barash Y., Shai O.

Genome Research. 18(8):1247–1258


Functional coordination of alternative splicing in the mammalian central nervous system

Fagnani M., Barash Y., Ip J.Y.

Genome Biology. 8:R108


CIS: compound importance sampling method for protein–DNA binding site p-value estimation

Barash Y., Elidan G., Kaplan T. Friedman N.

Bioinformatics. 21:596–600


Comparative analysis of algorithms

for signal quantitation from oligonucleotide microarrays

Barash Y., Dehan E., Krupsky M., Franklin W., Geraci M., Kaminski N.

Bioinformatics. 20:839–846

Sfp1 is a stressand nutrient-sensitive regulator of ribosomal protein gene expression

Marion R.M., Regev A., Segal E.

Barash Y., Koller D., Friedman N. O'Shea E.K.

Proceedings of the National Academy

of Sciences of the United States of America. 101:14315–14322


Modeling dependencies in

Protein-DNA binding sites

Barash Y., Elidan G., Friedman N.

Kaplan T.

Proc. of the 7th Annual International Conference on Research in Computational Molecular Biology (RECOMB)


Context-Specific Bayesian clustering

for Gene Expression Data

Barash Y., Friedman N.

Journal of Computational Biology: 169-191

From Promoter Sequence to Expression: A Probabilistic Framework

Segal E., Barash Y., Simon I., Friedman N. Keller D.

Proc. of the 6th Annual International Conference on Research in Computational Molecular Biology (RECOMB). :263–272


Context-Specific Bayesian clustering

for Gene Expression Data

Barash Y., Friedman N.

Proc. of the 5th Annual International Conference on Research in Computational Molecular Biology (RECOMB)

A Simple Hyper-Geometric Approach

for Discovering Putative Transcription Factor Binding Sites

Barash Y., Bejerano G., Friedman N.

Algorithms in Bioinformatics:

Proc. First International Workshop

(WABI). :278–293