14.10.2026. 15:15h, Faculty of Mathematics (online)

Ecological interactions in microbial communities alter mutant fitness globally and idiosyncratically

Dr. Michael Manhart

Department of Biochemistry and Molecular Biology, Rutgers University, USA

A meeting of the Bioinformatics seminar will be held on Wednesday, October 14th, starting at 15:15, in online classroom. Teachers and students of doctoral and master studies in computer science, mathematics, biology and other related disciplines are invited to join us.

LINK: https://zoom.us/j/2183428158?pwd=ouAZtpLrbPnOBsKjQiarS9Rh59fyqF.1

Abstract

The distribution of fitness effects (DFE) from spontaneous mutations characterizes an organism's evolutionary potential as well as its genomic functions. The DFE of a genome depends on the specific environment in which it is measured, and for microbes, a major feature of their environment is the presence of interactions with other species, such as competition for or cross-feeding of nutrients. Several recent studies have empirically measured how the DFE of one microbial species changes in the presence of interactions with other species. Since interactions in the human gut microbiome are known to shift significantly under many diseases, this raises the possibility that the microbiome's evolutionary fate may be greatly altered under those conditions. However, the underlying mechanisms by which interactions affect the DFE, and the statistical patterns they are expected to produce, remain unknown.

Here, we introduce a theoretical framework for classifying two ways in which an interaction can alter the DFE: (1) the interaction can alter the DFE globally (e.g., by changing its mean or variance) by modifying the community's overall growth rate and thus changing how quickly the population adapts; and (2) the interaction can affect individual mutants idiosyncratically when it shifts relative selection on traits for which mutants are pleiotropic, thereby changing which genes or pathways adapt. After predicting these effects and mechanisms using mathematical models of microbial communities, we demonstrate their empirical basis using high-throughput mutant phenotyping data across a range of microbial interactions. These results may help predict and potentially engineer evolutionary outcomes in microbial communities based on their ecological state.

Lecturer

Dr. Michael Manhart is an Assistant Professor in the Center for Advanced Biotechnology and Medicine, the Department of Biochemistry and Molecular Biology, and the Microbiome Program at Rutgers University Robert Wood Johnson Medical School. His lab studies quantitative evolutionary microbiology, with a particular focus on how fundamental evolutionary processes, such as mutation and selection, shape and are shaped by microbial ecology and physiology. Dr. Michael Manhart isalso broadly interested in theoretical biology, systems biology, and biophysics.

Seminar

The organizer of the seminar is BIRBI. The heads of the seminar are Prof. dr Nataša Pržulj and dr Jovana Kovačević.

22.4.2026. 15:15h, Faculty of Mathematics (online)

Shining light on structure and function in the dark protein universe

Dr Nicola Bordin

Tenure-Track Assistant Professor of Biochemistry, Università degli Studi di Padova, Italy

    Video: Recorded lecture (MP4, 44min, 100MB)

A meeting of the Bioinformatics seminar will be held on Wednesday, April 22nd, starting at 15:15, in online classroom. Teachers and students of doctoral and master studies in computer science, mathematics, biology and other related disciplines are invited to join us.

Please note that the seminar time has been moved to Wednesday, 15:15 CET this semester.

Abstract

The protein universe is vast, diverse, and still only partially explored, despite major advances in structure prediction and large-scale sequence analysis. A key challenge is the systematic characterization of this space in a way that captures structural diversity and the relationships between proteins at scale.

We will discuss a set of complementary approaches for exploring and organizing the protein universe. TED provides a large-scale structural decomposition of AlphaFold protein models into domains, defining a consistent vocabulary across hundreds of millions of structures. ContrasTED leverages contrastive learning to refine relationships between domains beyond traditional homology-based approaches. ProFam, a protein family language model, captures constraints within protein families and enables the generation of novel sequences consistent with those constraints.

Together, these approaches provide a framework for mapping, analysing, and engineering the protein universe.

Lecturer

Dr. Nicola Bordin did his Bachelor’s and Master in Biotechnology and Industrial Biotechnology at the University of Padua (Italy) with both dissertations in the fields of structural bioinformatics and functional genomics. He completed his PhD in Computational Biology and Bioinformatics on functional genomics in PVC bacteria at the Universidad Pablo de OIavide in Seville, Spain, under the supervision of Dr. Damien Devos. His fields of expertise are in algorithm design for protein function prediction, structure classification, sequence analyses and machine learning applied to protein data. After a period of postdoctoral research as senior researcher in the CATH team at University College London, where he developed novel algorithms for the functional classification of proteins and the structural classification of AlphaFold domains in CATH, he is currently a Tenure-Track Assistant Professor of Biochemistry at the University of Padua (Italy).

Seminar

The organizer of the seminar is BIRBI. The heads of the seminar are Prof. dr Nataša Pržulj and dr Jovana Kovačević.

25.3.2026. 15:15h, Faculty of Mathematics (online)

Single cell omics for personalized medicine in the age of artificial intelligence

Dr. Eduardo Beltrame

Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, UAE

    Video: Recorded lecture (MP4, 66min, 142MB)

A meeting of the Bioinformatics seminar will be held on Wednesday, March 25th, starting at 15:15, in online classroom. Teachers and students of doctoral and master studies in computer science, mathematics, biology and other related disciplines are invited to join us.

Please note that the seminar time has been moved to Wednesday, 15:15 CET this semester.

Abstract

One of the most exciting consequences of the accessibility of single cell omics technologies is their use in new experimental designs. Beyond atlases, longitudinal studies with many timepoints are also yielding unprecedented volumes and formats of data, with hundreds of millions of cells publicly available. Driven by steadily decreasing sequencing costs and streamlined experimental workflows, single cell omics technologies are now widely used from basic biological research to drug discovery and clinical studies.

I will present an overview of the emerging data and AI-models landscape in the field, together with novel clinical study designs enabled by lowering cost and complexity barriers, and current prospects from AI virtual cells to new developments in precision medicine and diagnostics. I will discuss emerging research directions for working with these growing volumes of single cell omics data at the newly established Computational Biology program at the Mohamed bin Zayed University of Artificial Intelligence in Abu Dhabi, and exciting opportunities at the intersection of artificial intelligence applied to biological data.

Lecturer

Eduardo da Veiga Beltrame is an Assistant Professor of Computational Biology at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi, where he is responsible for coordinating the new master’s and PhD programs in Computational Biology. His main research interest is the development of methods and tools to work with biological data generated by single-cell omics and their applications in precision medicine.

He holds a Ph.D. in Bioengineering from Caltech, where his primary line of research focused on developing experimental and computational methods and tools for single-cell RNA sequencing and its application to biological questions. Before joining MBZUAI, he was head of bioinformatics at ImYoo, a biotechnology startup spun out of Caltech research that conducts decentralized studies of the immune system using single-cell omics. Prior to ImYoo, Beltrame was a founding scientist at Retro Biosciences, a biotechnology startup dedicated to developing therapies for aging-related diseases.

His academic page is: https://mbzuai.ac.ae/study/faculty/eduardo-beltrame/

Seminar

The organizer of the seminar is BIRBI. The heads of the seminar are Prof. dr Nataša Pržulj and dr Jovana Kovačević.