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Jordan Brooker

dblp:156/9672 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1

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 › sequence analysis
DNA sequence analysis
0.212015
PseKNC-General: a cross-platform package for generating various modes of pseudo nucleotide compositions · Bioinform. 2015
Bioinformatics and computational biology › sequence analysis
sequence feature extraction
0.212015
PseKNC-General: a cross-platform package for generating various modes of pseudo nucleotide compositions · Bioinform. 2015

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

autocorrelation coefficients · 0.2
YearPublicationVenuePosition
2015 PseKNC-General: a cross-platform package for generating various modes of pseudo nucleotide compositions
abstract
SUMMARY: The avalanche of genomic sequences generated in the post-genomic age requires efficient computational methods for rapidly and accurately identifying biological features from sequence information. Towards this goal, we developed a freely available and open-source package, called PseKNC-General (the general form of pseudo k-tuple nucleotide composition), that allows for fast and accurate computation of all the widely used nucleotide structural and physicochemical properties of both DNA and RNA sequences. PseKNC-General can generate several modes of pseudo nucleotide compositions, including conventional k-tuple nucleotide compositions, Moreau-Broto autocorrelation coefficient, Moran autocorrelation coefficient, Geary autocorrelation coefficient, Type I PseKNC and Type II PseKNC. In every mode, >100 physicochemical properties are available for choosing. Moreover, it is flexible enough to allow the users to calculate PseKNC with user-defined properties. The package can be run on Linux, Mac and Windows systems and also provides a graphical user interface. AVAILABILITY AND IMPLEMENTATION: The package is freely available at: http://lin.uestc.edu.cn/server/pseknc.
Wei Chen 0064, Xitong Zhang, Jordan Brooker, Hao Lin 0001, Liqing Zhang 0002, Kuo-Chen Chou
Bioinform.3