Bioinformatics of carbonic anhydrases
The focus of this research consists of bioinformatic studies of carbonic anhydrases (CA), ubiquitous enzymes which are found in all kingdoms of life, focusing on CAs in animals. The ultimate goal is to increase our understanding of how and why various CA isoforms and CAs in different species are different from each other. This would be useful in understanding drug specificity, and in the design of novel, improved forms of CAs. An intermediate goal in this process is the discovery of most likely evolutionary histories of CAs.
The project is run by Martti Tolvanen in collaboration with the group of Seppo Parkkila (University of Tampere).
Conserved domain and evolution of secreted phospholipases A(2)
Secreted phospholipases A(2) (sPLA(2) s) are lipolytic enzymes present in organisms ranging from prokaryotes to eukaryotes but their origin and emergence are poorly understood. We study conserved domains of sPLA(2)
and proposed a model for their evolution.
Protein hydropathy predictions
We investigated the prediction accuracy of 56 hydropathy scales by correlating predicted values with the accessible surface area in known protein structures. Results for different amino acids vary greatly within each scale. We also investigated prediction accuracies of amino acids separately in secondary structural elements and in protein fold families.
Gene expression on the theory of phase synchronization
Using phase synchronization it is possible to detect biological
associations for gene pairs with cell cycle-specific expression profiles. Phase-synchronization clustering is able to detect biologically associated gene pairs that have linearly correlated (simultaneous and inverted) as well as time-delayed expression profiles.
Tools for the submission of mutations to databases and maintenance of locus-specific mutation databases. Advanced, integrated computer systems are needed to store and organize the increasing mutation information.
Turku BioNLP Group
The main focus of the BioNLP group is the development of text mining algorithms and their utilization in knowledge discovery in biology and medicine. The flagship resources developed by the group are the TEES text mining system which won several text mining competitions, and the EVEX resource comprising detailed information about genes, proteins, and their mutual relationships mined from the entire publicly available biomedical literature. The BioNLP group has a number of collaborative projects with universities worldwide.
More information about the group’s projects and publications can be found on its homepage.
Research utilizing the Auria biobank data
The Auria biobank is a project to centralize the storage of patient samples and related information from Turku area hospitals and to provide the means for scientists to utilize this large dataset for research purposes. The IT-department is involved in the Auria-project and we will utilize our expertise in machine learning and large scale data mining to apply the biobank data to different research questions.
- Parse me if you can: Artificial treebanks for parsing experiments on elliptical constructions
Droganova K., Zeman D., Kanerva J., Ginter F.
- Pain process of patients with cardiac surgery — Semantic annotation of electronic patient record data (2018)
Heikkilä Kristiina, Axelin Anna, Peltonen Laura-Maria, Heimonen Juho, Anttila Pauliina, Viljanen Timo, Salakoski Tapio, Salanterä Sanna
- Herbal Drug Use In Sickle Cell Disease Management; Trends And Perspectives In Sub-Saharan Africa (2018)
Okoh Michael P., Alli Lukman A., Tolvanen Martti E.E., Nwegbu Maxwell
- Ihmislähtöisyyden integrointi tietotekniikan diplomi-insinöörikoulutukseen (2018)
Johanna Isoaho, Jouni Isoaho, Seppo Virtanen, Tapio Salakoski
- Secondary use of electronic health records: Availability aspects in two Nordic countries (2018)
Vikström A., Moen H., Moosavi SR, Salakoski T., Salanterä S.
- Deep Learning for Assessing Banks’ Distress from News and Numerical Financial Data (2018)
Paola Cerchiello, Giancarlo Nicola, Samuel Rönnqvist, Peter Sarlin
- Sentiment in Citizen Feedback: Exploration by Supervised Learning (2018)
Robin Lybeck, Samuel Rönnqvist, Sampo Ruoppila
- A bottom-up analysis of sentence-initial DRDs in the Finnish Internet (2018)
Veronika Laippala, Aki-Juhani Kyröläinen, Filip Ginter, Jenna Kanerva, Johanna Komppa, JyrkiKalliokoski
- Mind the Gap: Data Enrichment in Dependency Parsing of Elliptical Constructions (2018)
Kira Droganova, Filip Ginter, Jenna Kanerva, Daniel Zeman
- Enhancing Universal Dependency Treebanks: A Case Study (2018)
Joakim Nivre, Paola Marongiu, Filip Ginter, Jenna Kanerva, Simonetta Montemagni, Sebastian Schuster, Maria Simi