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Olga Kirillova

dblp:10/2660 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2014
—ORCID · unresolved

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

Applied, interdisciplinary, general and emerging computing · 2 · 1 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
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
structural biology
0.112006
Map2mod - a server for evaluation of crystallographic models and their agreement with electron density maps · Bioinform. 2006
Bioinformatics and computational biology › structural bioinformatics
electron density map interpretation
0.012006
Map2mod - a server for evaluation of crystallographic models and their agreement with electron density maps · Bioinform. 2006
YearPublicationVenuePosition
2014 Using the CER Hub to ensure data quality in a multi-institution smoking cessation study
abstract
Comparative effectiveness research (CER) studies involving multiple institutions with diverse electronic health records (EHRs) depend on high quality data. To ensure uniformity of data derived from different EHR systems and implementations, the CER Hub informatics platform developed a quality assurance (QA) process using tools and data formats available through the CER Hub. The QA process, implemented here in a study of smoking cessation services in primary care, used the 'emrAdapter' tool programmed with a set of quality checks to query large samples of primary care encounter records extracted in accord with the CER Hub common data framework. The tool, deployed to each study site, generated error reports indicating data problems to be fixed locally and aggregate data sharable with the central site for quality review. Across the CER Hub network of six health systems, data completeness and correctness issues were prevalent in the first iteration and were considerably improved after three iterations of the QA process. A common issue encountered was incomplete mapping of local EHR data values to those defined by the common data framework. A highly automated and distributed QA process helped to ensure the correctness and completeness of patient care data extracted from EHRs for a multi-institution CER study in smoking cessation.
Kari L. Walker, Olga Kirillova, Suzanne E. Gillespie, David Hsiao, Valentyna Pishchalenko, Akshatha Kalsanka Pai, Jon Puro, Robert Plumley, Rustam Kudyakov, Art Allisany, MaryAnn McBurnie, Stephen E. Kurtz, Brian Hazlehurst
J. Am. Medical Informatics Assoc.2
2006 Map2mod - a server for evaluation of crystallographic models and their agreement with electron density maps
abstract
Abstract Summary: Here we report on recent developments of the map2mod server. It has been designed for validation of protein models created by X-ray data interpretation. It can also be used during the refinement process since it is able to indicate problem regions in the model. Apart from evaluation of model quality, it has an option to remove atoms of side chains, which are not consistent with the maps as well as improperly placed water molecules. There are two additional options: checking the B-factors of atoms in the provided model and comparison of R and Rfree values obtained as the result of refinement with the averages characteristic for the data resolution shell. Availability: The map2mod server is freely available for all user community (). Contact: olga,[email protected]
Olga Kirillova, Wladek Minor
Bioinform.1