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Norma H. Pawley

dblp:92/474 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2005
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1 · 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 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › structural biology
NMR spectroscopy
0.112005
APART: Automated Preprocessing for NMR Assignments with Reduced Tedium · Bioinform. 2005
Bioinformatics and computational biology › structural biology
resonance assignment
0.112005
APART: Automated Preprocessing for NMR Assignments with Reduced Tedium · Bioinform. 2005
Bioinformatics and computational biology
structural biology
0.112005
APART: Automated Preprocessing for NMR Assignments with Reduced Tedium · Bioinform. 2005
Bioinformatics and computational biology › epigenomics › ChIP-seq analysis
peak detection
0.012005
APART: Automated Preprocessing for NMR Assignments with Reduced Tedium · Bioinform. 2005

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

consensus filtering · 0.1
YearPublicationVenuePosition
2005 APART: Automated Preprocessing for NMR Assignments with Reduced Tedium
abstract
MOTIVATION: High-throughput NMR structure determination is a goal that will require progress on many fronts, one of which is rapid resonance assignment. An important rate-limiting step in the resonance assignment process is accurate identification of resonance peaks in the NMR spectra. Peak-picking schemes range from incomplete (which lose essential assignment connectivities) to noisy (which obscure true connectivities with many false ones). We introduce an automated preassignment process that removes false peaks from noisy peak lists by requiring consensus between multiple NMR experiments and exploiting a priori information about NMR spectra. This process is designed to accept multiple input formats and generate multiple output formats, in an effort to be compatible with a variety of user preferences. RESULTS: Automated preprocessing with APART rapidly identifies and removes false peaks from initial peak lists, reduces the burden of manual data entry, and documents and standardizes the peak filtering process. Successful preprocessing is demonstrated by the increased number of correct assignments obtained when data are submitted to an automated assignment program. AVAILABILITY: APART is available from http://sir.lanl.gov/NMR/APART.htm CONTACT: [email protected]; [email protected] SUPPLEMENTARY INFORMATION: Manual pages with installation instructions, procedures and screen shots can also be found at http://sir.lanl.gov/NMR/APART_Manual1.pdf.
Norma H. Pawley, Jason D. Gans, Ryszard Michalczyk
Bioinform.1