Fundamental Single Cell Data Analysis Workshop (In-person)

Adaikalavan Ramasamy

I use data to derive insights that can improve the quality of life.

By training, I am a statistician specializing in high dimensional data (i.e. number of parameters >> number of subjects) from biology, bioinformatics, epidemiology and to a more limited experience with clinical trials and finance. My software of choice is R (a free and powerful open source software), Unix tools (bash, awk, sed etc) and I am experienced with machine learning algorithms. I am learning python and deep learning techniques.

Some of my areas of expertise:

• Data cleaning, management and transformation
• Exploratory data analysis of very large datasets
• R programming
• Clustering or segmentation
• Linear reression (e.g. correlations, GLMs, ANOVA)
• Hypothesis or A/B testing (e.g. t-test, proportion test, Chi-square, p-value, confidence
  intervals, etc)
• Meta-analyses techniques (e.g. inverse-variance techniques, test of heterogeneity)
• Machine learning techniques (e.g. support vectors machines, linear discriminantanalysis, knn, decision trees etc)
• Visualizations (e.g. boxplots, heatmaps)

Gökçe Oğuz

My research interests involve studying functional genomics and its applications to human diseases. Trained as a hybrid research scientist with expertise in both wet-lab and dry-lab approaches, I have performed data analysis in disease related works and generated a series of novel scientific findings published in high impact factors journals, including Nature Medicine, Cancer Discovery, JEM and PNAS.

I am now a member of the Bioinformatics Consulting and Training Platform in Genome Institute of Singapore (GIS). I provide genomic analysis including bulk, single-cell RNAseq, microarray, and ChIP-seq data analysis through numerous collaborations and paid consultancy services over the last 4 years. To support the launch of GIS CODON+ Courses, I have curated and conducted genomic data science workshops for the researchers in A*STAR. We have trained more than 500 participants.

Jinmiao Chen

Dr Jinmiao Chen is a computational biologist with solid background in single-cell analysis and artificial intelligence (AI). She received her Bachelor degree in Data and Computer Science from Sun Yat- Sen (Zhongshan) University, China in 2002, PhD degree in artificial intelligence and computational biology from Nanyang Technological University, Singapore in 2007. During her PhD, she invented novel artificial neural network algorithms and published 1st-authored papers in top tier AI journals including IEEE Trans on Neural Network. After her PhD, she joined the Bioinformatics core of SIgN, A * STAR Singapore and she was able to analyse a wide range of data types including single- cell omics, flow/mass cytometry, microarray, next generation sequencing, microbiome /metagenomics and etc. Over the years, she has been an important pillar of the institute for Bioinformatics. In 2014, she became a Project Leader after a thorough selection and established her own research lab focusing on single-cell computational/system immunology. Since 2017, she has been a very productive and innovative Principal Investigator and leading the Single-Cell & AI for Precision Immunology (SCAIPI) lab. In her current team, she is supervising 8 postdoctoral research fellows, 2 data scientists, and 3 PhD students. One of her postdocs was awarded with Career Development Award in 2020. Since 2016, she has been an adjunct assistant professor at Department of Microbiology and Immunology, NUS.