Transcription Regulation and Cellular Phenotypes

Discovering novel SNPs that are correlated with patient outcome in a Singaporean cancer patient cohort treated with gemcitabine-based chemotherapy

Published date : 11 May 2018

Background
Single Nucleotide Polymorphisms (SNPs) can influence patient outcome such as drug response and toxicity after drug intervention. The purpose of this study is to develop a systematic pathway approach to accurately and efficiently predict novel non-synonymous SNPs (nsSNPs) that could be causative to gemcitabine-based chemotherapy treatment outcome in Singaporean non-small cell lung cancer (NSCLC) patients.

type
Journal Paper
journal
BMC Cancer (2018), 18:555, doi: 10.1186/s12885-018-4471-x
Impact Factor
3.288

A novel community driven software for functional enrichment analysis of extracellular vesicles data

Published date : 26 May 2017

Bioinformatics tools are imperative for the in depth analysis of heterogeneous high-throughput data. Most of the software tools are developed by specific laboratories or groups or companies wherein they are designed to perform the required analysis for the group. However, such software tools may fail to capture “what the community needs in a tool”. Here, we describe a novel community-driven approach to build a comprehensive functional enrichment analysis tool. Using the existing FunRich tool as a template, we invited researchers to request additional features and/or changes.

type
Journal Paper
journal
Journal of Extracellular Vesicles 2017, Vol. 6, 2017, Issue 1, doi: 10.1080/20013078.2017.1321455
Impact Factor
4.259

R-loopDB: a database for R-loop forming sequences (RLFS) and R-loops

Published date : 28 Nov 2016

R-loopDB (http://rloop.bii.a-star.edu.sg) was originally constructed as a collection of computationally predicted R-loop forming sequences (RLFSs) in the human genic regions. The renewed R-loopDB provides updates, improvements and new options, including access to recent experimental data. It includes genome-scale prediction of RLFSs for humans, six other animals and yeast. Using the extended quantitative model of RLFSs (QmRLFS), we significantly increased the number of RLFSs predicted in the human genes and identified RLFSs in other organism genomes.

type
Journal Paper
journal
Nucleic Acids Research, 2016, 1, doi: 10.1093/nar/gkw1054
Impact Factor
9.202

Big genomics and clinical data analytics strategies for precision cancer prognosis

Published date : 07 Nov 2016

The field of personalized and precise medicine in the era of big data analytics is growing rapidly. Previously, we proposed our model of patient classification termed Prognostic Signature Vector Matching (PSVM) and identified a 37 variable signature comprising 36 let-7b associated prognostic significant mRNAs and the age risk factor that stratified large high-grade serous ovarian cancer patient cohorts into three survival-significant risk groups.

type
Journal Paper
journal
Scientific Reports 6, 2016, Article no. 36493 (2016), doi:10.1038/srep36493