Integrated search and alignment of protein structures

Download

index.pdf

Date

2008-12-15

Author

Sacan, Ahmet
Toroslu, İsmail Hakkı
Ferhatosmanoglu, Hakan

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

174
views

0
downloads

Motivation: Identification and comparison of similar three-dimensional (3D) protein structures has become an even greater challenge in the face of the rapidly growing structure databases. Here, we introduce Vorometric, a new method that provides efficient search and alignment of a query protein against a database of protein structures. Voronoi contacts of the protein residues are enriched with the secondary structure information and a metric substitution matrix is developed to allow efficient indexing. The contact hits obtained from a distance-based indexing method are extended to obtain high-scoring segment pairs, which are then used to generate structural alignments.

Subject Keywords

Statistics and Probability, Computational Theory and Mathematics, Biochemistry, Molecular Biology, Computational Mathematics, Computer Science Applications

URI

https://hdl.handle.net/11511/37309

Journal

BIOINFORMATICS

DOI

https://doi.org/10.1093/bioinformatics/btn545

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

Integrating multi-attribute similarity networks for robust representation of the protein space Camoglu, Orhan; Can, Tolga; Singh, Ambuj K. (Oxford University Press (OUP), 2006-07-01) Motivation: A global view of the protein space is essential for functional and evolutionary analysis of proteins. In order to achieve this, a similarity network can be built using pairwise relationships among proteins. However, existing similarity networks employ a single similarity measure and therefore their utility depends highly on the quality of the selected measure. A more robust representation of the protein space can be realized if multiple sources of information are used.
LFM-Pro: a tool for detecting significant local structural sites in proteins Sacan, Ahmet; Ozturk, Ozgur; Ferhatosmanoglu, Hakan; Wang, Yusu (Oxford University Press (OUP), 2007-03-15) Motivation: The rapidly growing protein structure repositories have opened up new opportunities for discovery and analysis of functional and evolutionary relationships among proteins. Detecting conserved structural sites that are unique to a protein family is of great value in identification of functionally important atoms and residues. Currently available methods are computationally expensive and fail to detect biologically significant local features.
Finding differentially expressed genes for pattern generation Abul, O; Alhajj, R; Polat, Faruk; Barker, K (Oxford University Press (OUP), 2005-02-15) Motivation: It is important to consider finding differentially expressed genes in a dataset of microarray experiments for pattern generation. Results: We developed two methods which are mainly based on the q-values approach; the first is a direct extension of the q-values approach, while the second uses two approaches: q-values and maximum-likelihood. We present two algorithms for the second method, one for error minimization and the other for confidence bounding. Also, we show how the method called Pattern...
Implicit motif distribution based hybrid computational kernel for sequence classification Atalay, Mehmet Volkan (Oxford University Press (OUP), 2005-04-15) Motivation: We designed a general computational kernel for classification problems that require specific motif extraction and search from sequences. Instead of searching for explicit motifs, our approach finds the distribution of implicit motifs and uses as a feature for classification. Implicit motif distribution approach may be used as modus operandi for bioinformatics problems that require specific motif extraction and search, which is otherwise computationally prohibitive.
GLANET: genomic loci annotation and enrichment tool Otlu, Burcak; Firtina, Can; Keles, Sunduz; Tastan, Oznur (Oxford University Press (OUP), 2017-09-15) Motivation: Genomic studies identify genomic loci representing genetic variations, transcription factor (TF) occupancy, or histone modification through next generation sequencing (NGS) technologies. Interpreting these loci requires evaluating them with known genomic and epigenomic annotations.

Citation Formats

A. Sacan, İ. H. Toroslu, and H. Ferhatosmanoglu, “Integrated search and alignment of protein structures,” BIOINFORMATICS, pp. 2872–2879, 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/37309.