Centre for Computational Life Sciences (CCLS)
We will continue our popular seminar series online as long as the regulations concerning the Covid pandemic require this. We are planning the meetings on the 3rd Tuesday of the month at 2 pm, unless otherwise announced.
Tuesday 19 January at 2 pm: Jeroen Codée, Professor of Organic Chemistry, Leiden Institute of Chemistry, Leiden University
Title: Computation chemistry to understand reactive intermediated and direct stereoselective synthesis
Chemically synthesized carbohydrates (glycans/oligosaccharides) are indispensable in biochemical and medical research. Their synthesis is challenging because of the highly reactive intermediates that play an important role in connecting different carbohydrate building blocks. We have developed computational strategies to understand how the structure of these fleeting species governs their reactivity. Rather than studying a single example, we have mapped the reactivity of a large family of related species to establish structure-reactivity rules. The body of systematic experimental data that we are currently gathering may be used in the future to computationally predict the outcome of glycosylation reactions eventually enabling the in silico design of synthetic routes to fast-forward oligosaccharide synthesis and boost glycobiological and glycomedical research.
Tuesday 16 February at 2 pm: Joost Batenburg, Professor of Imaging and Visualisation, Leiden Institute for Advanced Computer Science, Leiden University
Title: Tomographic Techniques for Life Sciences
In this talk I will go over various types of tomographic imaging (CT scanning, electron tomography, optical tomography) that are used for biomedical and life science research. A key step in each of these imaging modalities is the tomographic reconstruction step, where the data acquired by the imaging instrument is turned into a 3D representation of the specimen. While this operation is usually hidden inside the instrument’s software, it can dramatically influence the resulting image quality, imaging artefacts, and as a result the ability to observe key internal processes with sufficient accuracy.
I will discuss various recent breakthroughs in algorithms and machine learning models that enable to compute high quality images from severely undersampled data, and to do so in real-time, leading to an interactive computational imaging instrument.
Thursday 18 March at 4 pm: Nataša Jonoska, University of South Florida, USA - Title Detecting complexities in a scrambled genome through spacial graphs
DNA rearrangement is a process found on both developmental and evolutionary scale. The process itself and the molecular shape at the time of the rearrangement can be modeled through 4-regular graphs. These graph models are illustrated through the rearrangement processes in a well studied ciliate species Oxytricha trifallax where DNA recombination is observed on a massive scale. Our studies show gene segments that recombine during DNA rearrangement processes may be organized on the chromosome in a variety of ways. They can overlap, interleave or one may be a subsegment of another. We use colored directed graphs to represent contigs containing rearranged segments where edges represent recombining segment organization. Using graph properties we associate a point in a higher dimensional Euclidean space to each graph such that cluster formations and analysis can be performed with various methods. The analysis shows some emerging graph structures indicating that segments of a single gene can interleave, or even contain, all of the segments from several other genes in between its segments.
Tuesday 20 April at 2 pm: Richard Allmendinger, The University of Manchester
Title: Experimental challenges in drug design and discovery optimization
Evaluating candidate solutions by conducting an experiment, e.g. a physical, biological or chemical experiment, can be expensive, time-consuming and resource intense. Drug development is a prime example where optimization relies on experiments. This talk will provide an overview of some non-standard challenges arising due to experiments, such as non-homogeneous per-objective evaluation times in a multi-objective problem, dynamic resource constraints, and non-static drug libraries in a drug discovery problem. Some existing techniques to cope with these challenges will be introduced, and, finally, promising areas of future work discussed.
Tuesday 18 May at 2 pm: TBA
Tuesday 15 June at 2 pm: TBA