Paul F. Long

dblp:30/6628 · DBLP profile ↗
← Back
2ranked-venue papers
0as first author
0since 2021 · last 2009
0000-0001-6698-4602ORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 2

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 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › computational microbiology
biosynthetic gene cluster analysis
0.112007
Polyketide synthase genes and the natural products potential of Dictyostelium discoideum · Bioinform. 2007
Bioinformatics and computational biology › genomics
genome analysis
0.112007
Polyketide synthase genes and the natural products potential of Dictyostelium discoideum · Bioinform. 2007
Bioinformatics and computational biology › drug discovery
natural product discovery
0.112007
Polyketide synthase genes and the natural products potential of Dictyostelium discoideum · Bioinform. 2007

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

sequence homology analysis · 0.1phylogenetic analysis · 0.1RT-PCR · 0.1
YearPublicationVenuePosition
2009 Clustering of protein domains for functional and evolutionary studies
abstract
BACKGROUND: The number of protein family members defined by DNA sequencing is usually much larger than those characterised experimentally. This paper describes a method to divide protein families into subtypes purely on sequence criteria. Comparison with experimental data allows an independent test of the quality of the clustering. RESULTS: An evolutionary split statistic is calculated for each column in a protein multiple sequence alignment; the statistic has a larger value when a column is better described by an evolutionary model that assumes clustering around two or more amino acids rather than a single amino acid. The user selects columns (typically the top ranked columns) to construct a motif. The motif is used to divide the family into subtypes using a stochastic optimization procedure related to the deterministic annealing EM algorithm (DAEM), which yields a specificity score showing how well each family member is assigned to a subtype. The clustering obtained is not strongly dependent on the number of amino acids chosen for the motif. The robustness of this method was demonstrated using six well characterized protein families: nucleotidyl cyclase, protein kinase, dehydrogenase, two polyketide synthase domains and small heat shock proteins. Phylogenetic trees did not allow accurate clustering for three of the six families. CONCLUSION: The method clustered the families into functional subtypes with an accuracy of 90 to 100%. False assignments usually had a low specificity score.
Pavle Goldstein, Jurica Zucko, Dusica Vujaklija, Anita Krisko, Daslav Hranueli, Paul F. Long, Catherine Etchebest, Bojan Basrak, John Cullum
BMC Bioinform.6
2007 Polyketide synthase genes and the natural products potential of Dictyostelium discoideum
abstract
MOTIVATION: The genome of the social amoeba Dictyostelium discoideum contains an unusually large number of polyketide synthase (PKS) genes. An analysis of the genes is a first step towards understanding the biological roles of their products and exploiting novel products. RESULTS: A total of 45 Type I iterative PKS genes were found, 5 of which are probably pseudogenes. Catalytic domains that are homologous with known PKS sequences as well as possible novel domains were identified. The genes often occurred in clusters of 2-5 genes, where members of the cluster had very similar sequences. The D.discoideum PKS genes formed a clade distinct from fungal and bacterial genes. All nine genes examined by RT-PCR were expressed, although at different developmental stages. The promoters of PKS genes were much more divergent than the structural genes, although we have identified motifs that are unique to some PKS gene promoters.
Jurica Zucko, N. Skunca, Tomaz Curk, Blaz Zupan, Paul F. Long, John Cullum, R. H. Kessin, Daslav Hranueli
Bioinform.5