Spark-IDPP: high-throughput and scalable prediction of intrinsically disordered protein regions with Spark clusters on the Cloud.
Bozena Malysiak-MrozekTomasz BaronDariusz MrozekPublished in: Clust. Comput. (2019)
Keyphrases
- high throughput
- disordered regions
- protein protein interactions
- amino acids
- protein function
- experimentally determined
- intrinsically disordered
- protein protein
- protein sequences
- amino acid sequences
- protein structure
- microarray
- mass spectrometry
- biological data
- secondary structure
- protein interaction
- mass spectrometry data
- systems biology
- genome wide
- predicting protein
- gene ontology
- molecular biology
- genomic data
- interaction networks
- proteomic data
- gene expression profiles
- protein structure prediction
- drug design
- data acquisition
- biological processes
- virtual screening
- protein complexes
- microarray data
- computational biology
- gene expression
- protein interaction networks
- protein folding
- sequence alignment
- cluster analysis
- sequence analysis
- functional modules
- ms ms
- protein interaction data
- machine learning
- biological knowledge
- spatial structure
- high precision
- computational methods