Applied Statistics and Data Science Seminars on Monday, January 13, 2025

Seminar 1

Title: Opportunities and Challenges in Single-Cell RNA-Seq: Revealing Biomarkers and Regulatory Networks in Early Brain Development

Venue and time: ISRT, 2:00 pm

Speaker: Dr. Md. Alamin, Assistant Professor, Department of Mathematics & Physics, School of Engineering and Physical Sciences, North South University

Abstract:

Unraveling the molecular mechanisms of early neuronal development is critical to understanding the genetic and regulatory factors driving human brain formation. Leveraging single-cell RNA sequencing (scRNA-seq), we profiled the transcriptional dynamics during the differentiation of human embryonic stem cells (hESCs) into neurons at two key time points: Day 26 (D26) and Day 54 (D54). Our analysis uncovered 539 differentially expressed genes (DEGs), revealing that up-regulated DEGs are involved in neurogenesis, while down-regulated DEGs play roles in synapse regulation. Reactome pathway analysis highlighted significant contributions of down-regulated DEGs to synaptic protein interactions. Furthermore, we identified 20 critical transcription factors and explored miRNA-DEG and TF-miRNA interactions, advancing our understanding of gene regulatory networks during early brain development. These findings offer valuable insights into the genetic underpinnings of intelligence, mental health, and neurodevelopmental disorders. Moreover, I will address the emerging challenges for statisticians and mathematicians in analyzing and interpreting high-dimensional single-cell data. These include handling data sparsity, developing robust computational models, and integrating multimodal datasets to uncover complex biological interactions. By bridging the gaps between biology, statistics, and mathematics, we can push the boundaries of our understanding and foster innovation in neuroscience research.

Seminar 2

Title: A reflection on the recent development of the subject area of Statistics and some specific issues of concern for further research

Venue and time: ISRT, 3:00 pm

Speaker: Dr. Moudud Alam, Associate Professor in Microdata Analysis, Dalarna University, Sweden

Abstract:

This talk is divided into two parts. In first part the recent development of the subject area of Statistics, particularly the development of Data Science, is discussed from the speaker’s experience along the way to develop a master’s and a PhD programme in Data Science, and Data Analytics at a Swedish university. The media outcry and the popularity of the computing technology, and artificial intelligence has pushed the Statistics community to rethink about its longstanding branding. Dedication of the 2024 Nobel prize in Physics and partly in Chemistry, to the contribution in the development of artificial neural network, and artificial intelligence can be considered as yet another dictation from the scientific community of the future direction of the filed. The contemporary labour market demands of the computing and soft skills is a non-negligible factor influencing the current trend of the subject. In this talk the experience of the speaker’s journey from Statistics to Data Science is discussed, in connection with the related Swedish and European initiatives. Yet, in this impassionate outrage it seems the scientific community is undermining (if not missing) the core assignment, as all researchers concentrate too much to the practical applications driven by the contemporary problems, mainly coming from the industry. In the second part, the speaker draws attention, using literature review and own research towards a number of statistical core issues that need special attention. In particular, the limitation of ad hoc (such as cross validation) inferential procedure is exemplified using variable selection problem as an example, from the literature. Using the speaker’s own research on service lifetime estimation of traffic signs in Sweden the speaker highlights the need for core statistical skills in dealing with unconventional data sources in the Data Science era.