Updates:

• ACM ICPS Proceedings link

• Videos of Keynotes are available now

##COVID-19 Update##

Even though COVID-19 is currently stable and under control in Thailand, CSBio2020 would remain an online conference that will take place virtually, based on the Bangkok, Thailand time zone of GMT/UTC +7.

CSBio2020 is a part of the activities and events in the AI Week in Bangkok, Thailand during Nov. 18-22, 2020, and collocating with ICONIP2020 and the 4th Deep Learning and AI Summer/Winter School (DLAI4).

ABOUT

With the advancement in next-generation molecular technology in generating the high-throughput “omics” data, life science has come to the era of “big data”. To extract biological knowledge from the data and translate it into benefits for society (e.g. better medicine and healthcare), novel and advanced computational tools are needed for data analysis. The current trends are to leverage AI and application of cognitive computing that combines domain knowledge with machine learning.

Call for Papers

The call for paper targets contribution in the field of computational approaches designed to face the challenges aroused by biological systems. It aims at giving an overview of the cutting-edge methods and tools to address biological systems. A Special Session on COVID-19 Health, Analytics, and Technologies (CHAT-2020) will provide an opportunity for global research linkages and experience sharing.

CSBio 2020 would like to invite researchers and industrial counterparts to meet at this event to exchange ideas and stimulate research collaborations.

Title: Genome-wide repeat expansions in complex disorders: beyond the coding sequence. [video]

Biography:

Title: Uncovering RNA and DNA Modifications from Native Sequences. [video]

Biography:

Intawat Nookaew is currently an Associate Professor in the Department of Biomedical Informatics at the University of Arkansas for Medical Sciences (UAMS) College of Medicine. He received his PhD degree Chemical Engineer from the King’s Mongkut’s University of Technology Thonburi, Thailand in 2007. In his thesis work, he focused on multilevel-omics data analysis and integration to study lipid metabolism of yeast at genome-scale level.  

After completing his PhD, he continued to have training as postdoctoral fellow (2008) in Chalmers University of Technology in Sweden in the area of Systems Biology in Biotechnology and Biomedical research. In 2012, he accepted the Assistant Professor and was promoted to be Associate Professor in 2014 in the Department of Chemical and Biological Engineering at Chalmers University of Technology in Sweden. He developed many useful bioinformatic software packages and web service that can be applied in broad applications.

In 2014, Intawat accepted a Senior Scientist position at Oak Ridge National Laboratory, TN, USA. He was a part of two big team science projects to which are Bioenergy Science Center, focused on development of consolidate bioprocess to produce biofuels from lignocellulosic materials and Plant Microbe Interface, focused on deeper understanding of beneficial interaction of microbial community and plant. 

In 2016, Intawat pursue his interest in Biomedical research, he accepted an Associate Professor in the Department of Biomedical Informatics (UAMS). While at UAMS, he has focused on development of computational/bioinformatical methods to advance the utilization of cutting-edge technologies for study RNA/DNA modifications and microbiome in Biotechnology and Biomedical research.      

Intawat has published over 130 peer-reviewed articles and book chapters. He was recently recognized by the Web of Science group for the quality of his research as a Highly Cited Researcher 2019. He has over 9,300 citations, H-index = 42, i-10 index = 83 based on Citation at Google Scholar.

Abstract:

Ribonucleotides modifications to mRNA play important roles biological regulations. Over 170 types of RNA modifications have been experimentally validated. Their detection traditionally relies on specific antibody-based enrichment and analytical chemistry tools; these approaches are labor intensive and can detect only one or a few modifications at a time. This is insufficient to truly assess complete transcriptomes for sequence-specific identification and quantitation of epigenetic signals. Recently, we were the first to use third-generation Oxford Nanopore Technology (ONT) sequencing to directly sequence cellular RNA in native from, at a transcriptomic level. We determined that the method can uncover RNA modifications of any type. Based on the principle that such modifications are absent on cDNA (6) or synthetical unmodified RNA, we conducted a study that compared sequence features of native modified RNA with unmodified RNA of the same sequence. We developed a bioinformatics tool, ELIGOS (Epitranscriptional Landscape Inferring from Glitches of ONT Signals), that successfully identified modified RNA bases from the native RNA sequences. ELIGOS accurately predicts known classes of RNA methylation sites (AUC > 0.93) in rRNAs from E. coli, yeast, and human cells, by using either unmodified in vitro transcribed RNA or our developed background-error model, which mimics the systematic error in native RNA sequences. The validity of the approach was illustrated in transcriptomes of yeast, mouse, and human cells.  We further apply ELIGOS in detection of DNA adducts and for distinguishing individual alkylated DNA adducts. We analyzed a library of 15 plasmids containing site-specifically inserted O6- or N2-alkyl-deoxyguanosine lesions differing in sizes, functional group and regiochemistries. Based on the native DNA sequences, ELIGOS can accurately identified the location of individual DNA adducts. Moreover, individual DNA adducts were clearly distinguished from each other at the signal level. ELIGOS software is publicly available and can be used to detect possible RNA and DNA modification sites at genome-scale from native RNA/DNA sequences.