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Zhaohua Xu

dblp:45/1759 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2007
—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
molecular marker development
0.112007
PIP: a database of potential intron polymorphism markers · Bioinform. 2007
Bioinformatics and computational biology › genomics
plant genomics
0.112007
PIP: a database of potential intron polymorphism markers · Bioinform. 2007

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

sequence homology · 0.1
YearPublicationVenuePosition
2007 PIP: a database of potential intron polymorphism markers
abstract
MOTIVATION: With the recent progress made in large-scale plant functional genome sequencing projects, a great amount of EST (express sequence tag) data is becoming available. With the help of complete genomic sequence information of model plants (rice and Arabidopsis), it is possible to predict the joints between adjacent exons after splicing (or termed 'intron positions' for short) in homologous ESTs of other plants. This would allow developing potential intron polymorphism (PIP) markers in these plants by designing primers in exons flanking the target intron. RESULTS: We have extracted a total of 57,658 PIP markers in 59 plant species and created a web-based database platform named PIP to provide detailed information of these PIP markers and homologous relationships among PIP markers from different species. The platform also provides a function of online designing of PIP markers based on cDNA/EST sequences submitted by users. With evaluations performed in silico, we have found that the intron position prediction is highly reliable and the polymorphism level of PIP markers is high enough for practical need. AVAILABILITY: http://ibi.zju.edu.cn/pgl/pip/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Long Yang 0003, Gulei Jin, Xiangqian Zhao, Zhaohua Xu
Bioinform.5