Publications | RISC Software GmbH
MethControl
(PDF) Genetic Algorithms: Theory and Applications
(PDF) Analyzing the Differences Between Reads and Contigs When Performing a Taxonomic Assignment Comparison in Metagenomics
High Performance, Cloud and Symbolic Computing in Big-Data problems applied to mathematical modeling of Comparative Genomics | MR.SYMBIOMATH Project | FP7 | CORDIS | European Commission
Drug-Induced Anaphylaxis | SpringerLink
Balázs Tukora
Projects – BITLAB
Weighted Epistatic Analysis of NSAIDs Hypersensitivity Data - ScienceDirect
(PDF) Mr.Cirrus: a map-reduce approach for high level cloud computing
Two-Level Parallelism to Accelerate Multiple Genome Comparisons | SpringerLink
Projects – BITLAB
Institute of Bioinformatics
Research Projects | JKU Linz
Projects | RISC Software GmbH
Bioinformatics with mobile devices - CORE
HapFABIA: identification of very short segments of identity by descent characterized by rare variants in large sequencing data. - Abstract - Europe PMC
Breaking the computational barriers of pairwise genome comparison. - Abstract - Europe PMC
Epistatic Analysis of Clarkson Disease - ScienceDirect
Two level parallelism and I/O reduction in genome comparisons | SpringerLink
Forschungsprojekte | JKU Linz
EU-Project LHCPhenoNet | RISC Software GmbH
AGEZ Hagenberg | RISC Software GmbH
E.T.S.I. INFORMÁTICA - TFG | Oferta líneas | Ing. Informática (Tecnologías de la Información) - University of Malaga
Systems biology approaches to enhance our understanding of drug hypersensitivity reactions, Clinical & Experimental Allergy | 10.1111/cea.12371 | DeepDyve
Review: High-performance computing to detect epistasis in genome scale data sets | Briefings in Bioinformatics | Oxford Academic
HapFABIA: Identification of very short segments of identity by descent characterized by rare variants in large sequencing data | Nucleic Acids Research | Oxford Academic
Bioinformatics software, shifting to mobility - CORE
Docencia
2012 - LRZ
Review: High-performance computing to detect epistasis in genome scale data sets | Briefings in Bioinformatics | Oxford Academic