Disruptive AI Technologies for Molecular Biology and Medicine: DNA Motifs, CRISPR-Cas9 Off-Targets, and Cancer Screening from Blood

Speaker:        Prof. Ka-Chun Wong
                City University of Hong Kong

Title:          "Disruptive AI Technologies for Molecular Biology and
                 Medicine: DNA Motifs, CRISPR-Cas9 Off-Targets,
                 and Cancer Screening from Blood"

Date:           Tuesday, 9 July 2019

Time:           3:00pm - 4:00pm

Venue:          Room 1409 (near lift no. 25/26), HKUST

Abstract:

In this talk, I will present my research group contributions in
bioinformatics and health informatics in recent years. In particular, the
unconventional and disruptive AI technologies are focused.

Firstly, the DNA binding of transcription factors is central to gene
regulation and stem cell development. The DNA binding pattern (i.e. DNA
motif) elucidation of transcription factors forms the basis for downstream
research. Therefore, I will present our breakthroughs in elucidating DNA
binding patterns from the protein-coding sequences of transcription
factors using AI as well as our synthetic biology approach to synthesize a
heterodimeric DNA motif from two monomeric DNA motifs. A DNA motif
published on Nature has been rescued.

Secondly, CRISPR-Cas9 is the predominant tool for gene editing and raised
substantial concerns on its clinical implications. To avoid any side
effect, its off-target predictions are fundamentally essential. I will
present our recent work in predicting CRISPR-Cas9 off-targets using deep
learning, the latest AI technology.

Finally, I will present our very recent work in screening cancers from
blood. I will demonstrate how our proposed AI approach (CancerA1DE) can
outperform the existing approach (CancerSEEK) proposed in John Hopkins
University. In particular, our approach can double the existing
sensitivity from 38% to 77% for the earliest cancer detection (i.e., Stage
I) at the 99% specificity level. This is part of the "ACM Distinguished
Speaker Lecture" series and the official ACM link can be found here
https://speakers.acm.org/lectures/12385.


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Biography:

Ka-Chun Wong is a professor at City University of Hong Kong. He finished
his PhD degree in Department of Computer Science at University of Toronto
(where modern AI was popularized in 2010s) within 3.5 years (2012-13
departmental average: 6 years after master degree) by the end of 2014,
after his RGC-funded MPhil degree. He is merited as the youngest associate
editor as well as first ever outside USA and Germany for the
open-peer-review journal, BioData Mining, in 2016. He is also on the
editorial board of Applied Soft Computingsince 2016. He was invited as the
plenary/keynote speakers for ICBCB 2017, ISACIT 2018, DSIT 2019, and
IC-LYCS 2019. In addition, he has solely edited 2 books published by
Springer and CRC Press, attracting 30 peer-reviewed book chapters around
the world (i.e. Argentina, Australia, Belgium, Brazil, China, Egypt,
France, Germany, Hong Kong, India, Japan, Spain, and USA). In 2017 and
2018, he has single-authored DNA motif informatics published on
Bioinformatics and iScience with CityU affiliation, demonstarating solid
examples for his PhD students at CityU. After that, he led his CityU team
to pursue the direction further as published on Nucleic Acids Research
(2017 IF=11.6) with CityU affiliation in 2019.