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Author: liuzlab

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Collaborative work published in Cell.

  30.07.2014   News

Congratulations to Ying-Wooi Wan.  Her collaborative work with Dr. Bellen’s lab was accepted by Cell.

A grant from Hearing Health Foundation.

  25.04.2014   News

A grant from hearing health foundation has been awarded to us in collaboration with the Groves lab to study the hair cell regeneration.

Our paper is highlighted by Nature Methods

  31.03.2014   News

NATURE METHODS | RESEARCH HIGHLIGHTS | METHODS IN BRIEF GENOMICS miRNA profiling depends on platform Nature Methods 11, 369 (2014) doi:10.1038/nmeth.2905 Published online 28 March 2014 Wan, Y.-W. et al. PLoS One 9, e87782

Our Paper is noted by GenomeWeb.com

  17.03.2014   News

Our study on the Cancer Genome Atlas (TCGA) project was noted by genome web.com http://www.genomeweb.com/sequencing/last-weeks-clinical-sequencing-papers-note-13

Our research in BCM news

  10.02.2014   News

Tools produce different answers in microRNA profiles When researchers at Baylor College of Medicine (www.bcm.edu) sought to mine The Cancer Genome Atlas for information on the effects of small bits

On the reproducibility of miRNA profiling techniques.

  6.02.2014   News, Paper

Our study on the reproducibility between miRNA microarray and sequencing technology was published in PLOS ONE [PDF].  This study found that large percentage of miRNAs demonstrated poor correlation between the

Paper on combinatorial drug therapy was accepted by Bioinformatics as an original research article.

  27.01.2014   Paper

Kaifang’s paper on combinatorial drug therapy through mixed integer linear programming was accepted for publication in Bioinformatics as an original research article.

Welcome, Denise!

  22.01.2014   News

Welcome to Denise who has now formally joined our group as a postdoctoral fellow!

Congratulations to Andrew for passing his qulification exam.

  21.01.2014   Other

Congratulations to Andrew for passing his qulification exam.

Two CIBR Awards

  13.12.2013   Other

We just got two collaborative awards with Sardiello and Mirjana Maletic-Savatic lab.  These two grants will enable us to generate a strong set of preliminary data for our future grants.

Our research in Rice news!

  15.11.2013   News

http://news.rice.edu/2013/11/13/new-statistical-tools-being-developed-for-mining-cancer-data/

William won the 1st place in Graduate Student Research Symposium.

  17.10.2013   Other

Congratulations to William who just won the 1st place in Graduate Student Research Symposium!

Paper accepted by IEEE GENSIPS 2013.

  20.09.2013   Paper

Our paper titled ‘IDENTIFYING CANCER BIOMARKERS THROUGH A NETWORK REGULARIZED COX MODEL’ has been accepted as a regular paper to be presented in the 2013 IEEE International Workshop on Genomic

Paper accepted by HMG

  13.09.2013   Paper

Congratulations to Sangeetha and Wooi.  Their paper on  ” NLRP7 affects trophoblast lineage differentiation, binds to overexpressed YY1 and alters CpG methylation” was accepted by Human Molecular Genetics.

An NSF Grant Awarded

  4.09.2013   Grants

National Science Foundation DMS-1263932 collaborative grant to study “Statistical Methods for Integrated Analysis of High-Throughput Biomedical Data”, September 2013-2017, with Genevera Allen and Pradeep Ravikumar. In the joint DMS/NIGMS Initiative

Wen received an ICIBM 2013 Student & Trainee Travel Award

  1.07.2013   Other

Congrats to Wen Zhang who has been chosen to receive an ICIBM 2013 Student & Trainee Travel Award.

LogitLapnet accepted by BMC Genomics!

  10.06.2013   Paper

Congrats to Wen Zhang and Wooi Wan for their manuscript “Molecular pathway identification using biological network-regularized logistic models” that was accepted by BMC Genomcis!

Our collaborative work was published in JCEM

  23.05.2013   Paper

Expression and Functional Pathway Analysis of Nuclear Receptor NR2F2 in Ovarian Cancer http://jcem.endojournals.org/content/early/2013/05/20/jc.2013-1081.abstract

William got the NLM training fellowship

  14.05.2013   Other

Congratulations to William Choi! He was selected as one of the two recipients of the NLM Biomedical Informatics fellowship.

Congratulations to Drs. Wan and Anderson!

  14.05.2013   Paper

Our paper on “Expression and Functional Pathway Analysis of Nuclear Receptor NR2F2 in Ovarian Cancer”  was accepted by The Journal of Clinical Endocrinology & Metabolism.

Our Collaborative work on Mecp2 and its miRNA regulator is the cover of Genes & Development.

  7.03.2013   Other

Human-specific regulation of MeCP2 levels in fetal brains by microRNA miR-483-5p http://genesdev.cshlp.org/content/27/5/485.abstract

Our paper on digital sorting for gene expression deconvolution is accepted by BMC Bioinformatics!

  4.03.2013   Paper

Our paper on LLGM was accepted by IEEE Transactions on NANOBIOSCIENCE.

  13.11.2012   Paper

Our paper on LLGM was accepted by IEEE Transactions on NANOBIOSCIENCE.

Congratulations to Marco!!!!

  23.09.2012   Other

Congratulations to our collaborator Marco! Our R01 is funded by NIH.  We will work with the Sardiello lab to study TFEB functions on lysosomal diseases.

NIPS paper accepted!!!

  3.09.2012   Paper

Congratulations to Eunho, Pradeep and Genevera.  Our paper on “Graphical Models via Generalized Linear Models” was accepted by NIPS 2012 There were a record 1467 submissions to NIPS this year,

Paper accepted by IEEE BIBM

  5.06.2012   Paper

Our recent paper on Poisson Graphical Network was accepted by IEEE BIBM 2012 as a full article! Congrats!

CIBR award.

  9.11.2011   Grants

We were just awarded a Baylor College of Medicine Computational and Integrative Biomedical Research Seed Grant for a proposal entitled, “Integrating Genetic Networks to Discover Biomarkers for Glioblastoma”.  The grant is for

Paper accepted by Nature Methods

  7.11.2011   Paper

Congratulations to Yi Zhong. Our paper on gene expression deconvolution in linear space was accepted by Nature methods.  Good job!

Welcome

  3.10.2010   Other

Welcome to the Liu Lab at Baylor College of Medicine. Our lab develops bioinformatics approaches for analyzing high throughput biological data, such as gene expression arrays, RNA-seq and genomic sequencing