New developments in the InterPro database

Mulder, Nicola; Apweiler, Rolf; Attwood, Teresa K.; Bairoch, Amos Marc; Bateman, Alex; Binns, David; Bork, Peer; Buillard, V.; Cerutti, Lorenzo; Copley, Richard R.; Courcelle, Emmanuel; Das, Ujjwal; Daugherty, Louise C.; Dibley, Mark; Finn, Robert D.; Fleischmann, Wolfgang; Gough, Julian; Haft, Daniel H.; Hulo, Nicolas; Hunter, Sarah; Kahn, Daniel; Kanapin, Alexander; Kejariwal, Anish; Labarga, Alberto; Langendijk-Genevaux, Petra S.; Lonsdale, David; López, Rodrigo; Letunić, Ivica; Madera, Martin; Maslen, John; McAnulla, Craig; McDowall, Jennifer; Mistry, Jaina; Mitchell, Alex L.; Nikol'skaya, A. N.; Orchard, Sandra; Orengo, Christine A.; Petryszak, Robert; Selengut, Jeremy D.; Sigrist, Christian J. A.; Thomas, Paul D.; Valentin, Franck; Wilson, Derek A.; Wu, Chuang; Yeats, Corin

doi:10.1093/nar/gkl841

Cited by 471 publications

(370 citation statements)

References 23 publications

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“…More precisely, each protein has been associated to a binary feature vector, representing a protein profile, whose [3] Motif fingerprints InterPro [45] Protein families, domains and functional sites EggNOG [46] Non-supervised Orthologous Groups Pfam [19] Protein domain Swiss-Prot [5] Manually curated keywords describing the function of the proteins Protein superfamilies [23] Structural and functional annotations elements are 1 when the protein is annotated for a specific feature (e.g. includes a specific domain, or a specific motif), and 0 otherwise.…”

Section: Datamentioning

confidence: 99%

Learning node labels with multi-category Hopfield networks

Frasca

Bassis

Valentini

2015

Neural Comput & Applic

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In several real-world node-label prediction problems on graphs, in fields ranging from computational biology to World-Wide-Web analysis, nodes can be partitioned into categories different from the classes to be predicted, on the basis of their characteristics or their common properties. Such partitions may provide further information about node classification that classical machine learning algorithms do not take into account. We introduce a novel family of parametric Hopfield networks (m-Category Hopfield Networks) and a novel algorithm (Hopfield Multi-Category -HoMCat), designed to appropriately exploit the presence of propertybased partitions of nodes into multiple categories. Moreover, the proposed model adopts a cost-sensitive learning strategy to prevent the remarkable decay in performance usually observed when instance labels are unbalanced, that is when one class of labels is highly under-represented than the other one. We validate the proposed model on both synthetic and real-world data, in the context of multi-species function prediction, where the classes to be predicted are the Gene Ontology terms and the categories the different species in the multi-species protein network. We carried out an intensive experimental validation, which on the one hand compares HoMCat with several state-of-the-art graph-based algorithms, and on the other hand reveals that exploiting meaningful prior partitions of input data can substantially improve classification performances.

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Section: Datamentioning

confidence: 99%

Learning node labels with multi-category Hopfield networks

Frasca

Bassis

Valentini

2015

Neural Comput & Applic

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“…In silico methods Domain predictions were made using InterProScan (Mulder et al, 2007), HTH program (Dodd and Egan, 1990) and BLASTP (Altschul et al, 1990). Precise length of the domains was determined using CDD (Marchler-Bauer et al, 2007).…”

Section: Integrating Promoter Fusions On the M Acetivorans Chromosomementioning

confidence: 99%

Regulation of putative methyl‐sulphide methyltransferases in Methanosarcina acetivorans C2A

Bose

Kulkarni

Metcalf

2009

Molecular Microbiology

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SummaryThe regulation of the Methanosarcina acetivorans mtsD, mtsF and mtsH genes, which encode putative corrinoid/methyltransferase isozymes involved in methylsulphide metabolism, was examined by a variety of methods, suggesting that their expression is regulated at both the transcriptional and posttranscriptional levels. Transcripts of all three genes, measured by quantitative reverse transcription PCR, were shown to be most abundant during growth on methanol with dimethylsulphide (DMS). Transcript levels were also high in media with CO or methylamines, but much lower with methanol. In contrast, translational fusions to mtsD showed high expression levels on CO or methanol with DMS, while the mtsF translational fusion showed highest reporter gene activity on methylamines with much lower expression on CO or methanol with DMS. The activity of mtsD and mtsF fusions was very low when the strains were grown in methanol or acetate. Expression of the mtsH fusion was not detected on any substrate, despite the presence of an mRNA transcript. The transcription start sites of all three genes were determined by 5Ј-RACE revealing large leader sequences for each transcript. Characterization of deletion mutants lacking putative regulatory genes suggests that MA0862 (msrF), MA4383 (msrC) and MA4560 (msrG) act as transcriptional activators of mtsD, mtsF and mtsH respectively.

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“…Both D. immitis clusters and, for comparison, C. elegans complete gene-set (WORMPEP v140) were mapped to the Gene Ontology (GO) terms (The Gene Ontology Consortium, 2000;Mulder et al, 2005). In total, GO terms were assigned to 341 (19%) D. immitis clusters and 12,681 (64%) C. elegans genes, respectively.…”

Section: Functional Categorization and Other Sequence Analysismentioning

confidence: 99%

Identification and analysis of genes expressed in the adult filarial parasitic nematode Dirofilaria immitis

Yin

Martin

McCarter

et al. 2006

International Journal for Parasitology

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The heartworm Dirofilaria immitis is a filarial parasitic nematode infecting dogs and other mammals worldwide causing fatal complications. Here, we present the first large-scale survey of the adult heartworm transcriptome by generation and analysis of 4005 expressed sequence tags, identifying about 1800 genes and expanding the available sequence information for the parasite significantly. Brugia malayi genomic data offered the most valuable information to interpret heartworm genes, with about 70% of D. immitis genes showing significant similarities to the assembly. Comparative genomic analyses revealed both genes common to metazoans or nematodes and genes specific to filarial parasites that may relate to parasitism. Characterization of abundant transcripts suggested important roles for genes involved in energy generation and antioxidant defense in adults. In particular, we proposed that adult heartworm likely adopted an anaerobic electron transfer-based energy generation system distinct from the aerobic pathway utilized by its mammalian host, making it a promising target in developing next generation macrofilaricides and other treatments. Our survey provided novel insights into the D. immitis transcriptome and laid a foundation for further comparative studies on biology, parasitism and evolution within the phylum Nematoda. q

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New developments in the InterPro database

Cited by 471 publications

References 23 publications

Learning node labels with multi-category Hopfield networks

Learning node labels with multi-category Hopfield networks

Regulation of putative methyl‐sulphide methyltransferases in Methanosarcina acetivorans C2A

Identification and analysis of genes expressed in the adult filarial parasitic nematode Dirofilaria immitis

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