Pål Sætrom

Orcid: 0000-0001-8142-7441

According to our database1, Pål Sætrom authored at least 16 papers between 2003 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2020
PyRanges: efficient comparison of genomic intervals in Python.
Bioinform., 2020

2019
epic2 efficiently finds diffuse domains in ChIP-seq data.
Bioinform., 2019

2014
Circular RNAs are depleted of polymorphisms at microRNA binding sites.
Bioinform., 2014

The eGenVar data management system - cataloguing and sharing sensitive data and metadata for the life sciences.
Database J. Biol. Databases Curation, 2014

2012
Single Nucleotide Polymorphisms Can Create Alternative Polyadenylation Signals and Affect Gene Expression through Loss of MicroRNA-Regulation.
PLoS Comput. Biol., 2012

2010
A two-step site and mRNA-level model for predicting microRNA targets.
BMC Bioinform., 2010

2008
Meta-analysis of breast cancer microarray studies in conjunction with conserved <i>cis</i>-elements suggest patterns for coordinate regulation.
BMC Bioinform., 2008

2007
Motif kernel generated by genetic programming improves remote homology and fold detection.
BMC Bioinform., 2007

Reliable prediction of Drosha processing sites improves microRNA gene prediction.
Bioinform., 2007

2006
The Petacomp Machine: A MIMD Cluster for Parallel Pattern-mining.
Proceedings of the 2006 IEEE International Conference on Cluster Computing, 2006

2005
Hardware accelerated genetic programming for pattern mining in strings.
PhD thesis, 2005

Evolutionary Rule Mining in Time Series Databases.
Mach. Learn., 2005

2004
A recursive MISD architecture for pattern matching.
IEEE Trans. Very Large Scale Integr. Syst., 2004

Predicting the efficacy of short oligonucleotides in antisense and RNAi experiments with boosted genetic programming.
Bioinform., 2004

2003
The Role of Discretization Parameters in Sequence Rule Evolution.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2003

Mining Interesting Temporal Rules with Genetic Programming and Specialized Hardware.
Proceedings of the 2003 International Conference on Machine Learning and Applications, 2003


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