Joint Bioconductor Asia - Hong Kong Bioinformatics Symposium
Website: https://biocasia2023.bioconductor.org/
Venue: Boardroom, 1/F, Faculty Administration Wing (FAW), LKS Faculty of Medicine, 21 Sassoon Road
Programme drafted on 13/10/2023

R/Bioconductor workshops
Oct 15 (Sun),
09:30-17:30
Oct 16 (Mon),
14:30-17:30
Oct 16 (Mon),
14:30-17:30

RNA-seq analysis with R/Bioconductor
Dr David Shih, Mr Jonathan Tse and Ms Noel Yue, The University of Hong KongSeminar Room 2, 4/F, No. 3 Sassoon RoadSCDNEY: Unlocking insights for single-cell and spatial data with scFeatures
Dr Yue Cao and Mr Andy, University of Sydney
Lecture Theatre 2, G/F, William M.W. Mong Block, 21 Sassoon Road
Analysing CRISPR screens with MAGeCK and edgeR
Dr Göknur Giner, Walter and Eliza Hall Institute of Medical Research (WEHI) & U Melbourne
Lecture Theatre 3, G/F, William M.W. Mong Block, 21 Sassoon Road

Monday, 16 Oct 2023 (HKT)
09:00 - 09:05
09:05 - 10:05
09:05 - 09:35
09:35 - 09:50
09:50 - 10:05
10:05 - 10:20
10:20 - 11:20
10:20 - 10:50
10:50 - 11:05

11:05 - 11:20
11:20 - 11:35
11:35 - 12:50
11:35 - 11:50
11:50 - 12:05
12:05 - 12:20
12:20 - 12:35

WelcomeSession 1: Statistical modelling - chaired by Dr Yuanhua Huang
Evolving an ecosystem for scalable genomic data science
Prof Vincent Carey, Harvard University
Improved Estimation of Functional Enrichment in SNP Heritability Using Feasible Generalized
Least Squares
Mr Zewei Xiong
Systems approach for congruence and selection of cancer models towards precision medicine
Dr Jian Zou, Chongqing Medical University
Coﬀee BreakSession 2: Statistical genetics - chaired by Dr Yingying Wei
High-Dimensional Causal Mediation in Imaging Genetics Study
Prof George Tseng, University of Pittsburgh
A statistical method for Cross-population ﬁne-mapping by leveraging genetic diversity andaccounting for confounding bias
Dr Mingxuan Cai, City University of Hong Kong
Functional Adaptive Double-Sparsity Estimator for Functional Linear Regression with Applicationin Wearable Sensor Data Analysis
Dr Xinyue Li, City University of Hong Kong
Coﬀee BreakSession 3: Cancer and Therapeutics - chaired by Dr David Shih
Identifying predictors of glioma evolution from longitudinal sequencing
Dr Quanhua Mu, The Hong Kong University of Science and Technology
Epigenetic cancer drug facilitates the proteogenomics discovery of immunotherapy targets
Dr Stephen Li, The University of Hong KongUnmasking LUAD’s Vulnerabilities: Targeting AURKA-TPX2 Interaction for Innovative Therapeutics
Dr MUKUNTHAN KS, Manipal Institute of Technology
Integrative Epigenomics and Transcriptomics Analysis to Identify Signature Biomarkers of Lung
Adenocarcinoma
Mr Arnab Mukherjee, Manipal Institute of Technology

112:35 - 12:50(ﬂash talks)

12:50 - 14:30
14:30 - 17: 30

2(1) Epigenetic clock CpGs are associated with chromatin and are enriched at enhancers
Mr Yik Chai Charles Lau(2) Copy number state minimum evolutionary path algorithm for inferring whole genome
doublings
Mr Wai Tung Jonathan Tse(3) Transcriptomic analysis of cisplatin resistance in ovarian cancer
Ms Noel Yue(4) Comprehensive genomic characterization of EBV-associated carcinomas
Ms Yucan ChenLunch
HikingTuesday, 17 Oct 2023 (HKT)
09:00 - 09:05
09:05 - 10:05
09:05 - 09:35
09:35 - 09:50
09:50 - 10:05
10:05 - 10:20
10:20 - 11:20
10:20 - 10:50
10:50 - 11:05
11:05 - 11:20
11:20 - 11:35
11:35 - 12:20
11:35 - 11:5011:50 - 12:05

12:05 - 12:20(ﬂash talks)

12:20 - 12:50

12:50 - 14:00

WelcomeSession 4: Single-cell dynamics - chaired by Dr Yuanhua Huang
Exploring Cell Fate and Memory through Single-Cell Multi-Omic Lineage Tracing
Dr Shou-Wen Wang, Westlake University
Covidscope: An atlas scale COVID‚Äì19 resource for single-cell meta analysis at sample andcellular levels
Ms Danqing (Angela) Yin, The University of Hong Kong
Temporal preserved representation learning from time-series single-cell transcriptomics data
Ms Yijun Liu, The University of Hong Kong
Coﬀee BreakSession 5: Single-cell genomics - chaired by Dr Jiguang Wang & Prof Jean Yang
Identiﬁcation of potential neural precursor cell populations using atlas-level single-cell data
Prof Zhichao Miao, Guangzhou National Laboratory
Annotating and discovering cell types from single cell RNA-seq data using machine learning
Dr Yu Li , The Chinese University of Hong Kong
JSNMF enables eﬀective and accurate integrative analysis of single-cell multiomics data
Prof Zhixiang Lin, The Chinese University of Hong KongCoﬀee BreakSession 6: Single-cell analytics - chaired by Dr Zhixiang LinDiﬀerential inference for single-cell RNA-sequencing data
Dr Fangda Song, The Chinese University of Hong Kong, Shenzhen
Spatiotemporal transcriptomic and genomic analysis reveals waves of hematopoiesis in humanembryonic organoids
Ms Yiming Chao, 1. The University of Hong Kong, HKSAR 2. Centre for Translational Stem CellBiology, HKSAR 3. Wellcome-MRC Cambridge Stem Cell Institute, UK(1) Unveiling the Complexity: The Current State of Single-Cell Benchmarking
Dr Yue Cao(2) Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-speciﬁcgene analysis
Ms Yixuan Wang(3) Deciphering sequence-informed regulatory patterns from single-cell multi-omics
Ms Fangxin Cai(4) Con-AAE: contrastive cycle adversarial autoencoders for single-cell multi-omics alignmentand integration
Mr Xuesong Wang
Session 7: Hong Kong Bioinformatics Community Forum - chaired by Dr Joshua Ho
Discuss the development of bioinformatics community in Hong Kong,
Open forum hosted by Dr Joshua Ho for all participants, including bioinformatics researchers andstudents
Lunch

3

14:00 - 15:10
14:00 - 14:15

14:15 - 14:30
14:30 - 14:45
14:45 - 15:00

15:00 - 15:10(ﬂash talks)

15:10 - 15:25
15:25 - 16:30
15:25 - 15:55
15:55 - 16:10
16:10 - 16:25
16:25 - 16:30(ﬂash talks)
16:30 - 16:45
16:45 - 17:45
16:45 - 17:15
17:15 - 17:30
17:30 - 17:45
17:45 - 18:00

4Session 8: Spatial transcriptomics and imaging - chaired by Dr Can Yang / Dr Lequan Yu
Biologically-informed self-supervised learning for segmentation of subcellular spatialtranscriptomics data
Dr Xiaohang Fu, The University of Sydney
Benchmarking translational potential of spatial transcriptomics imputation from histology
imagesMs Chuhan Wang, The University of Sydney
Systematic comparison of sequencing-based spatial transcriptomic methods
Dr Luyi Tian, Guangzhou Laboratory
CellContrast: Reconstructing Spatial Relationships in Single-Cell RNA Sequencing Data via Deep
Contrastive Learning
Dr Shumin Li, The University of Hong Kong
(1) Decoding Fine-grained Cellular Architectures from Histology Images
Mr Weiqin Zhao
(2) Towards the Visual-Transcriptomics Foundation Model for Spatial Transcriptomics Analysis
Ms Zhuo Liang(3) Multi-task learning for Blastocyst Quality Assessment
Ms Lu YuCoﬀee BreakSession 9: Biotechnology computation- chaired by Dr Joshua HoExperiment-guided clustering to unravel complex drug-diet interactions in nutriomics data
Prof Jean Yang, University of Sydney
Cell-type aware CRISPR editing outcomes prediction
Mr Weizhong Zheng, The University of Hong Kong
Integrating long-read RNA sequencing improves locus-speciﬁc quantiﬁcation of transposable
element expression
Ms Sojung Lee, The University of Hong Kong
(1) Improving long-read scRNA-seq data analysis with FLAMESMr Changqing WangCoﬀee BreakSession 10: General bioinformatics - chaired by Dr Jason Wong
Biodiversity Genomics - From evolution to conservation policyProf Jerome Hui, The Chinese University of Hong Kong
Lipidomic signatures of resilience to coronary artery disease learnt from chimpanzees
Mr Andy Tran, University of Sydney
TDbasedUFE and TDbasedUFEadv: bioconductor packages to perform tensor decomposition
based unsupervised feature extraction
Prof Y-h. Taguchi, Chuo UniversityRemarks