Organisation and staff

Ola Spjuth

senior lecturer at Department of Pharmaceutical Biosciences, Research; Pharmaceutical Bioinformatics

Email:
ola.spjuth[AT-sign]farmbio.uu.se
Telephone:
+4618-471 4281
Mobile phone:
+46 70 4250628
Visiting address:
Room BMC D3:2 Uppsala biomedicinska centrum BMC, Husarg. 3
Postal address:
Box 591
751 24 UPPSALA

deputy director at Department of Information Technology, Uppsala Multidisciplinary Centre for Advanced Computational Science

Email:
ola.spjuth[AT-sign]uppmax.uu.se
Mobile phone:
+46 70 4250628
Visiting address:
ITC, Lägerhyddsvägen 2, hus 4
752 37 Uppsala
Postal address:
Box 337
751 05 Uppsala

Short presentation

Research focused on pharmaceutical bioinformatics and computational pharmacology, and more specifically predictive toxicology and -metabolism. Deputy director at UPPMAX center for high-performance computing, and head of the Bioinformatics Compute and Storage Facility (UPPNEX) at Science for Life Laboratory Bioinformatics.

 

Keywords: bioinformatics machine learning pharmaceutical bioinformatics predictive modeling predictive toxicology predictive metabolism

My courses

Biography


PhD in Bioinformatics from Uppsala University, 2009. Postdoctoral fellowships at Karolinska Institutet, Stockholm and Finnish Institute of Molecular Medicine (FIMM), Helsinki. Currently employed as Senior Lecturer at Department of Pharmaceutical Biosciences in the fields of data-intensive and translational bioinformatics with a particular focus on how modern e-infrastructures enables the studying of complex phenomena, and predictive modeling in pharmacology, toxicology, and metabolism. Also, co-director at the UPPMAX high performance computing center at Uppsala University, and heading the Bioinformatics Compute and Storage facility at Science for Life Laboratory in Sweden.

Research

High-throughput technologies have transformed biomedicine into a data-intensive discipline. This has shifted the focus from traditional data generation and hypothesis testing to more data-driven research, and bioinformatics data analysis has become the bottleneck in many projects. However, the field is characterized by growing data sets and poorly scalable software, threatening to severely constrain many biomedical projects. Our group aims at developing new methods and applications to meet the demands of high-throughput biology and drug discovery, using high-throughput and cloud-based e-infrastructures and Big Data analytics.

Publications

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