Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Finding differentially expressed genes for pattern generation
Download
index.pdf
Date
2005-02-15
Author
Abul, O
Alhajj, R
Polat, Faruk
Barker, K
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
208
views
0
downloads
Cite This
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 Patterns from Gene Expression (PaGE) (Grant et al., 2000) can benefit from q-values. Finally, we conducted some experiments to demonstrate the effectiveness of the proposed methods; experimental results on a selected dataset (BRCA1 vs BRCA2 tumor types) are provided
Subject Keywords
Statistics and Probability
,
Computational Theory and Mathematics
,
Biochemistry
,
Molecular Biology
,
Computational Mathematics
,
Computer Science Applications
URI
https://hdl.handle.net/11511/48041
Journal
BIOINFORMATICS
DOI
https://doi.org/10.1093/bioinformatics/bti189
Collections
Department of Computer Engineering, Article
Suggestions
OpenMETU
Core
Integrated search and alignment of protein structures
Sacan, Ahmet; Toroslu, İsmail Hakkı; Ferhatosmanoglu, Hakan (Oxford University Press (OUP), 2008-12-15)
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 ...
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.
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.
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.
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.
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
O. Abul, R. Alhajj, F. Polat, and K. Barker, “Finding differentially expressed genes for pattern generation,”
BIOINFORMATICS
, pp. 445–450, 2005, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/48041.