Prediction of Enzymatic Properties of Protein Sequences Based on the EC Nomenclature

Date

2017-07-20

Author

Dalkıran, Alperen
Doğan, Tunca
Rifaioğlu, Ahmet Süreyya
Atalay, Mehmet Volkan
Martin, Maria Jesus
Atalay, Rengül

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https://www.iscb.org/ismbeccb2017
https://hdl.handle.net/11511/85441

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Prediction of Enzymatic Properties of Protein Sequences Based on the EC Nomenclature Dalkıran, Alperen; Rifaioğlu, Ahmet Süreyya; Doğan, Tunca; Atalay, Mehmet Volkan; Martin, Maria Jesus; Atalay, Rengül (null; 2017-06-30)
Prediction of enzymatic properties of protein sequences based on the enzyme commission nomenclature Dalkıran, Alperen; Atalay, Mehmet Volkan; Atalay, Rengül; Department of Computer Engineering (2017) The volume of expert manual annotation of biomolecules is steady due to high costs associated with it, although the number of sequenced genomes continues to grow exponentially. Computational methods have been proposed in order to predict the attributes of gene products. The prediction of Enzyme Commission (EC) numbers is a challenging issue in this area. Enzymes have crucial roles in metabolic pathways, therefore they are widely employed in biotechnological and biomedical pplications. EC numbers are numeric...
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Prediction of the effects of single amino acid variations on protein functionality with structural and annotation centric modeling Cankara, Fatma; Tunçbağ, Nurcan; Department of Bioinformatics (2020) Whole-genome and exome sequencing studies have indicated that genomic variations may cause deleterious effects on protein functionality via various mechanisms. Single nucleotide variations that alter the protein sequence, and thus, the structure and the function, namely non-synonymous SNPs (nsSNP), are associated with many genetic diseases in human. The current rate of manually annotating the reported nsSNPs cannot catch up with the rate of producing new sequencing data. To aid this process, automated compu...
Prediction of protein subcellular localization based on primary sequence data Özarar, Mert; Atalay, Mehmet Volkan; Department of Computer Engineering (2003) Subcellular localization is crucial for determining the functions of proteins. A system called prediction of protein subcellular localization (P2SL) that predicts the subcellular localization of proteins in eukaryotic organisms based on the amino acid content of primary sequences using amino acid order is designed. The approach for prediction is to nd the most frequent motifs for each protein in a given class based on clustering via self organizing maps and then to use these most frequent motifs as features...

Citation Formats

A. Dalkıran, T. Doğan, A. S. Rifaioğlu, M. V. Atalay, M. J. Martin, and R. Atalay, “Prediction of Enzymatic Properties of Protein Sequences Based on the EC Nomenclature,” 2017, Accessed: 00, 2021. [Online]. Available: https://www.iscb.org/ismbeccb2017.