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Diana L. Kolbe

dblp:79/7066 · DBLP profile ↗
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5ranked-venue papers
2as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 5 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
4 papers
Bioinformatics and computational biology · 83% Medical and health informatics · 17%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › structural bioinformatics › nucleic acid structure analysis
RNA structural alignment
0.222011
Fast filtering for RNA homology search · Bioinform. 2011
Local RNA structure alignment with incomplete sequence · Bioinform. 2009
Medical and health informatics
clinical genomics
0.212014
Cordova: Web-based management of genetic variation data · Bioinform. 2014
Bioinformatics and computational biology › biological database
genetic variation database
0.212014
Cordova: Web-based management of genetic variation data · Bioinform. 2014
Bioinformatics and computational biology › sequence alignment
local alignment
0.112009
Local RNA structure alignment with incomplete sequence · Bioinform. 2009
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics › RNA structure
RNA secondary structure
0.112009
Infernal 1.0: inference of RNA alignments · Bioinform. 2009
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics
RNA structure
0.112009
Local RNA structure alignment with incomplete sequence · Bioinform. 2009

Methods — techniques the papers use, named apart from their topics

covariance model · 0.2vector-parallel implementation · 0.1multi-segment CYK · 0.1CYK algorithm · 0.1
YearPublicationVenuePosition
2014 Cordova: Web-based management of genetic variation data
abstract
UNLABELLED: Cordova is an out-of-the-box solution for building and maintaining an online database of genetic variations integrated with pathogenicity prediction results from popular algorithms. Our primary motivation for developing this system is to aid researchers and clinician-scientists in determining the clinical significance of genetic variations. To achieve this goal, Cordova provides an interface to review and manually or computationally curate genetic variation data as well as share it for clinical diagnostics and the advancement of research. AVAILABILITY AND IMPLEMENTATION: Cordova is open source under the MIT license and is freely available for download at https://github.com/clcg/cordova.
Sean S. Ephraim, Nikhil Anand, Adam P. DeLuca, Kyle R. Taylor, Diana L. Kolbe, Allen C. Simpson, Hela Azaiez, Christina M. Sloan, A. Eliot Shearer, Andrea R. Hallier, Thomas L. Casavant, Todd E. Scheetz, Richard J. H. Smith, Terry A. Braun
Bioinform.5
2011 Fast filtering for RNA homology search
abstract
MOTIVATION: Homology search for RNAs can use secondary structure information to increase power by modeling base pairs, as in covariance models, but the resulting computational costs are high. Typical acceleration strategies rely on at least one filtering stage using sequence-only search. RESULTS: Here we present the multi-segment CYK (MSCYK) filter, which implements a heuristic of ungapped structural alignment for RNA homology search. Compared to gapped alignment, this approximation has lower computation time requirements (O(N⁴) reduced to O(N³), and space requirements (O(N³) reduced to O(N²). A vector-parallel implementation of this method gives up to 100-fold speed-up; vector-parallel implementations of standard gapped alignment at two levels of precision give 3- and 6-fold speed-ups. These approaches are combined to create a filtering pipeline that scores RNA secondary structure at all stages, with results that are synergistic with existing methods.
Diana L. Kolbe, Sean R. Eddy
Bioinform.1
2009 Local RNA structure alignment with incomplete sequence
abstract
MOTIVATION: Accuracy of automated structural RNA alignment is improved by using models that consider not only primary sequence but also secondary structure information. However, current RNA structural alignment approaches tend to perform poorly on incomplete sequence fragments, such as single reads from metagenomic environmental surveys, because nucleotides that are expected to be base paired are missing. RESULTS: We present a local RNA structural alignment algorithm, trCYK, for aligning and scoring incomplete sequences under a model using primary sequence conservation and secondary structure information when possible. The trCYK algorithm improves alignment accuracy and coverage of sequence fragments of structural RNAs in simulated metagenomic shotgun datasets. AVAILABILITY: The source code for Infernal 1.0, which includes trCYK, is available at http://infernal.janelia.org.
Diana L. Kolbe, Sean R. Eddy
Bioinform.1
2009 Infernal 1.0: inference of RNA alignments
abstract
SUMMARY: INFERNAL builds consensus RNA secondary structure profiles called covariance models (CMs), and uses them to search nucleic acid sequence databases for homologous RNAs, or to create new sequence- and structure-based multiple sequence alignments. AVAILABILITY: Source code, documentation and benchmark downloadable from http://infernal.janelia.org. INFERNAL is freely licensed under the GNU GPLv3 and should be portable to any POSIX-compliant operating system, including Linux and Mac OS/X.
Eric P. Nawrocki, Diana L. Kolbe, Sean R. Eddy
Bioinform.2
2009 Infernal 1.0: inference of RNA alignments
abstract
Bioinformatics (2009) 25(10), 1335–1337 We regret that the above paper was published with the wrong copyright line. The correct copyright line for this Open Access paper should have been: The Author 2009. Published by Oxford University Press. All rights reserved.
Eric P. Nawrocki, Diana L. Kolbe, Sean R. Eddy
Bioinform.2