H
Hari Krishna Yalamanchili
Researcher at Baylor College of Medicine
Publications - 50
Citations - 943
Hari Krishna Yalamanchili is an academic researcher from Baylor College of Medicine. The author has contributed to research in topics: Biology & Medicine. The author has an hindex of 16, co-authored 37 publications receiving 636 citations. Previous affiliations of Hari Krishna Yalamanchili include Boston Children's Hospital & Li Ka Shing Faculty of Medicine, University of Hong Kong.
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Journal ArticleDOI
Tau-Mediated Disruption of the Spliceosome Triggers Cryptic RNA Splicing and Neurodegeneration in Alzheimer's Disease.
Yi-Chen Hsieh,Caiwei Guo,Hari Krishna Yalamanchili,Measho Abreha,Rami Al-Ouran,Yarong Li,Eric B. Dammer,James J. Lah,Allan I. Levey,David A. Bennett,Philip L. De Jager,Philip L. De Jager,Nicholas T. Seyfried,Zhandong Liu,Zhandong Liu,Joshua M. Shulman +15 more
TL;DR: It is shown that loss of function in SmB, encoding a core spliceosomal protein, causes decreased survival, progressive locomotor impairment, and neuronal loss, independent of Tau toxicity, and genetic disruption of these factors enhances Tau-mediated neurodegeneration in AD.
Journal ArticleDOI
Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models
Qiumin Tan,Qiumin Tan,Hari Krishna Yalamanchili,Hari Krishna Yalamanchili,Jeehye Park,Jeehye Park,Antonia De Maio,Hsiang Chih Lu,Ying Wooi Wan,Ying Wooi Wan,Joshua J. White,Joshua J. White,Vitaliy V. Bondar,Vitaliy V. Bondar,Layal S. Sayegh,Layal S. Sayegh,Xiuyun Liu,Xiuyun Liu,Yan Gao,Yan Gao,Roy V. Sillitoe,Harry T. Orr,Zhandong Liu,Huda Y. Zoghbi +23 more
TL;DR: It is reported that constitutive deletion of RBM17, which encodes an RBP with a putative role in splicing, causes early embryonic lethality in mice and that its loss in Purkinje neurons leads to rapid degeneration, and proposed that repression of cryptic splicing by RBPs is critical for neuronal health and survival.
Journal ArticleDOI
Inferring gene regulatory networks by integrating ChIP-seq/chip and transcriptome data via LASSO-type regularization methods
TL;DR: Two extended models of LASSO, L0 and L1/2 regularization models are applied to infer gene regulatory network from both high-throughput gene expression data and transcription factor binding data in mouse embryonic stem cells to demonstrate the efficiency and applicability of these two models.
Journal ArticleDOI
Transcriptional Regulation by ATOH1 and its Target SPDEF in the Intestine
Yuan-Hung Lo,Eunah Chung,Zhaohui Li,Ying-Wooi Wan,Maxime M. Mahe,Min-Shan Chen,Taeko K. Noah,Kristin N. Bell,Hari Krishna Yalamanchili,Tiemo J. Klisch,Zhandong Liu,Joo-Seop Park,Noah F. Shroyer +12 more
TL;DR: The direct targets of ATOH1 are unveiled in the adult intestines and the transcriptional events that initiate the specification and function of intestinal secretory lineages are illuminated.
Proceedings ArticleDOI
An ultra-fast and scalable quantification pipeline for transposable elements from next generation sequencing data.
TL;DR: SalmonTE, a fast and reliable pipeline for the quantification of TEs from RNA-seq data, is developed and benchmarked against TEtranscripts, a widely used TE quantification method, and three other quantification methods using several RNA- sequencing datasets from Drosophila melanogaster and human cell-line.