Date: February 14 and 15
Hour: From 10 a.m. to 11 a.m.
Venue: Online (via ZOOM)
«The OLISSIPO project – Fostering Computational Biology Research and Innovation in Lisbon – is pleased to announce the upcoming lectures on February 14 and 15, with Prof. Jonas Almeida (National Cancer Institute) and Prof. Dan Gusfield (University of California), respectively.
February 14
Prof. Jonas Almeida
Title: “Universal Sequence Maps, from biological sequences to numbers and back”
Abstract: Universal Sequence Maps (USM) are an iterated mapping technique that can represent sequence succession in a manner that is both bijective and scale-free. In its original unidirectional form, proposed in 1990 as Chaos Game Representation (CGR), it was proposed as a graphical representation of gene structure that borrowed methodologically from statistical mechanics of complex dynamic phenomena. Over a decade later, CGR was found to provide an alignment-free route to sequence analysis that generalizes Markovian succession. In the subsequent 2 decades, new properties were uncovered and the iterated technique was reformulated, as reviewed in this presentation. Intriguingly, the modern bidirectionally iterated form, USM, appears to offer a convenient route to develop language models of Biological sequences for generative AI applications.
Biosketch: I hold the position of (tenured) Senior investigator and Data Science director at the National Cancer Institute, Division of Cancer Epidemiology and Genetics (NIH/NCI intramural program). I also maintain academic positions at the State University of New York (SUNY – Stony Brook), Queen’s University Belfast, UK, and George Mason University in Virginia. I started my academic career at the University of Lisbon (PhD Biological Engineering, 1995), where I remain involved in collaborative initiatives towards Artificial intelligence, Cloud Computing, and the development of consumer-facing polygenic risk calculators for Precision Prevention.
February 15
Prof. Dan Gusfield
Title: “Integer Linear Programming and SAT-Solving in Computational Biology”
Abstract: In this talk I will explain how to use Integer Linear Programming for problems in computational biology, focussing on the problem of RNA folding. This approach has been very successful for a wide range of problems in computational biology. In writing a book on integer programming in computational biology (2019), I examined in depth about 50 such problems. Most solved successfully with ILP. However, there were a few that did not. Then students and I tried using SAT-solving on those harder problems and found that it was more successful on those problems than was ILP, giving another computational tool for computational biology that complements ILP.
Biosketch: Prof. Emeritus Dan Gusfield started work in computational biology (around 1982) before the field had a name. He is a Fellow of the ISCB and ACM and was the founding Editor-in-chief of the IEEE/ACM Transactions on Computational Biology and Bioinformatics, and wrote three books on topics in computational biology (plus two others including one that appeared just last week: Proven Impossible). He wrote the first paper indexed in PubMed with the term “computational biology”. He worked (part-time) at the first DOE Human Genome Center (before NIH became involved in the HGP) and was on the three-person (animal, vegetable, mineral) committee that wrote the proposal to establish the Genome Center at UC Davis, resulting in the largest building on the UCD campus, and hiring of multiple new faculty at UC Davis.
