I received a Ph.D. in Biochemistry in 2006 (Åbo Akademi University, Finland). Since 2008, I have served as group leader in the CDR where he leads the Computational Drug Discovery Group. My main interests are computational drug discovery, molecular modeling, sequence-structure-function relationships in proteins, and membrane proteins (especially G protein-coupled receptors and transporters).
I am leading the Pharmaceutical Design and Discovery Unit.
I obtained my PhD at the University of Nancy in 2010 in the field of Chemoinformatics. I have worked in both academic and industrial projects. Since then I work as a expert Chemoinformatician for the Drug Discovery and Chemical Biology Consortium (DDCB, under the HILIFE/EU-openscreen).
My research interest computer artificial intelligence, in particular databases and machine learning. I am also routinely using molecular modeling and virtual screen tools.
The focus of my work is :
I am now postoctoral researcher working for the SUDDEN project.
During my PhD, with a background in biology, I have first worked in the classification of GPCRs. I have them moved to structural analysis and docking studies, then to partly work in the lab to study early receptor orexin evolution (collaboration with Prof. Kukkonen). Thus in addition to being acquainted with computational applications, I am experienced in pharmacology and molecular biology. I have also conducted virtual screen and experimental hit validation and pathway analysis on the Toll-like receptor ligands. I have conducted a research visit in Monash University (Melbourne, AUS) as part of my PhD studies.
My research interests G protein-coupled receptors, orexin receptors, protein sequence mining, molecular evolution, phylogenetic reconstruction, molecular pharmacology, and computational drug discovery.
In my free time, I play roller derby in Helsinki Roller Derby All-Stars, and I have also played for Team Finland in two previous World Cups. Additionally I do gym, horseback riding and hanging out with my two dogs Rölli and Piku.
I have a B.Sc. in software engineering followed by a M.Sc. in bioinformatics from the University of Turku (FI). I have been working in start-up companies as a developer before starting my PhD studies. I have experience in data mining, data analysis and machine learning as well as web development (including as team leader).
My research interests are in the developement of chemogenomics and chemoinformatic tools. I am particularly interested into recent developments of machine learning to conduct predictive modeling and data analysis.
My project is about the development and integration of chemical databases, for example the IDAAPM data (Legehar et al., 2016), see http://idaapm.helsinki.fi
I am also involved in the discovery of novel quorum sensing inhibitors and antibacterial compounds using virtual screens, structural modeling (docking studies) and QSAR modeling (in collaboration with the groups of Prof. Jari Yli-Kauhaluoma (medicinal chemistry) and Docent Adyary Fallerero (in vitro studies).
I am a chemoinformatician with a BSc in computer science, MSc in pharmacy (University of Helsinki), and work experience as a data scientist from a major company. I have advanced programming skills with particular insights in homology modeling and membrane proteins (see Grazhdankin et al., J. Struct. Biol., 2019).
My research interests are tied to artificial intelligence and machine learning, and to Bayesian and graph-based theories. I seek to solve challenging problems in multi-objective optimization of molecular complexes. In addition, I work on a hit-to-lead optimization (confidential, funded by Business-Finland TUTL).
I graduated in from the University of Paris-Diderot (Paris 7) with a master in cheminformatics (in-silico drug design (external link)). From August 2018 I have been working in the Xhaard group.
My research interest are the methods to convert chemical knowledge into numbers. I am experienced and sometimes enjoy coding in Python and R.
My project aims to devise efficient scoring based functions. I am working with refernece states, atom types, and the ability to introduce and score water molecules. Simultaneously, I am working on the design of inhibitor for the membrane-bound pyrophosphatase. I conduct follow-up similarity screens and virtual screens, and conduct through computational simulation a fragment-based optimization in connection with medicinal chemists from the Yli-Kauhaluoma group.
In free time, I go bouldering and also play volley ball. I eat a lot of goodies too.
I am from the French city of Nantes where I followed a training the Ecole Centrale, a competitive engineer school in the French system. Following a final year internship in the group, I followed up as a PhD student. I enjoy learning on anything that is even remotely related to physics, biology or a bunch of other research fields, thus making me an easy target for nerd-sniping. That's also how I ended up here starting from my computer-science-focused background.
My research interests are connected to digital science, in particular machine learning and the use of graphs in chemoinformatics applications. As part of the SUDDEN project, I am building computational data analysis tools to mine and analyze pharmaceutically active ingredients in the environment (circulating water and waste water, activated sludge) with aim to drive policy making. I believe that the field would benefit from data integration and standardization.
There is generally 1-3 M.Sc. rotating students in the lab, especially in spring time. We are welcoming regularly summer workers, interns and erasmus students (typically at M2 internship). We have had students form Greece (Thessalonica), France (Nantes, Paris, Toulouse), Italy (Urbino, Padova), as well as summer workers from Finland (University of Helsinki/University of Eastern Finland).
Currently: Lauri Urvas (UH Faculty of Pharmacy, researcher line; see picture); for the spring 2020 two more students are expected (erasmus exchange to University Paris-Sorbonne, Master ISDD, and University of Nantes).
[Updated November 2019]
PhD theses (second supervisor)
Visiting PhD students
[*] continuation in the group as PhD student.