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Showing 1 to 12 of 109 entries
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Pleurochrysome: A Web Database of Pleurochrysis Transcripts and Orthologs Among Heterogeneous Algae.

Plant & cell physiology

Yamamoto N, Kudo T, Fujiwara S, Takatsuka Y, Hirokawa Y, Tsuzuki M, Takano T, Kobayashi M, Suda K, Asamizu E, Yokoyama K, Shibata D, Tabata S, Yano K.
PMID: 26746174
Plant Cell Physiol. 2016 Jan;57(1):e6. doi: 10.1093/pcp/pcv195. Epub 2016 Jan 07.

Pleurochrysis is a coccolithophorid genus, which belongs to the Coccolithales in the Haptophyta. The genus has been used extensively for biological research, together with Emiliania in the Isochrysidales, to understand distinctive features between the two coccolithophorid-including orders. However, molecular...

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Yamamoto N, Kudo T, Fujiwara S, et al. Pleurochrysome: A Web Database of Pleurochrysis Transcripts and Orthologs Among Heterogeneous Algae. Plant Cell Physiol. 2016;57(1):e6doi: 10.1093/pcp/pcv195.
Yamamoto, N., Kudo, T., Fujiwara, S., Takatsuka, Y., Hirokawa, Y., Tsuzuki, M., Takano, T., Kobayashi, M., Suda, K., Asamizu, E., Yokoyama, K., Shibata, D., Tabata, S., & Yano, K. (2016). Pleurochrysome: A Web Database of Pleurochrysis Transcripts and Orthologs Among Heterogeneous Algae. Plant & cell physiology, 57(1), e6. https://doi.org/10.1093/pcp/pcv195
Yamamoto, Naoki, et al. "Pleurochrysome: A Web Database of Pleurochrysis Transcripts and Orthologs Among Heterogeneous Algae." Plant & cell physiology vol. 57,1 (2016): e6. doi: https://doi.org/10.1093/pcp/pcv195
Yamamoto N, Kudo T, Fujiwara S, Takatsuka Y, Hirokawa Y, Tsuzuki M, Takano T, Kobayashi M, Suda K, Asamizu E, Yokoyama K, Shibata D, Tabata S, Yano K. Pleurochrysome: A Web Database of Pleurochrysis Transcripts and Orthologs Among Heterogeneous Algae. Plant Cell Physiol. 2016 Jan;57(1):e6. doi: 10.1093/pcp/pcv195. Epub 2016 Jan 07. PMID: 26746174; PMCID: PMC4722176.
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Detection of gene annotations and protein-protein interaction associated disorders through transitive relationships between integrated annotations.

BMC genomics

Masseroli M, Canakoglu A, Quigliatti M.
PMID: 26046679
BMC Genomics. 2015;16:S5. doi: 10.1186/1471-2164-16-S6-S5. Epub 2015 Jun 01.

BACKGROUND: Increasingly high amounts of heterogeneous and valuable controlled biomolecular annotations are available, but far from exhaustive and scattered in many databases. Several annotation integration and prediction approaches have been proposed, but these issues are still unsolved. We previously...

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Masseroli M, Canakoglu A, Quigliatti M. Detection of gene annotations and protein-protein interaction associated disorders through transitive relationships between integrated annotations. BMC Genomics. 2015;16:S5doi: 10.1186/1471-2164-16-S6-S5.
Masseroli, M., Canakoglu, A., & Quigliatti, M. (2015). Detection of gene annotations and protein-protein interaction associated disorders through transitive relationships between integrated annotations. BMC genomics, 16S5. https://doi.org/10.1186/1471-2164-16-S6-S5
Masseroli, Marco, et al. "Detection of gene annotations and protein-protein interaction associated disorders through transitive relationships between integrated annotations." BMC genomics vol. 16 (2015): S5. doi: https://doi.org/10.1186/1471-2164-16-S6-S5
Masseroli M, Canakoglu A, Quigliatti M. Detection of gene annotations and protein-protein interaction associated disorders through transitive relationships between integrated annotations. BMC Genomics. 2015;16:S5. doi: 10.1186/1471-2164-16-S6-S5. Epub 2015 Jun 01. PMID: 26046679; PMCID: PMC4460591.
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A disease similarity matrix based on the uniqueness of shared genes.

BMC medical genomics

Carson MB, Liu C, Lu Y, Jia C, Lu H.
PMID: 28589854
BMC Med Genomics. 2017 May 24;10:26. doi: 10.1186/s12920-017-0265-2.

BACKGROUND: Complex diseases involve many genes, and these genes are often associated with several different illnesses. Disease similarity measurement can be based on shared genotype or phenotype. Quantifying relationships between genes can reveal previously unknown connections and form a...

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Carson MB, Liu C, Lu Y, et al. A disease similarity matrix based on the uniqueness of shared genes. BMC Med Genomics. 2017;10:26doi: 10.1186/s12920-017-0265-2.
Carson, M. B., Liu, C., Lu, Y., Jia, C., & Lu, H. (2017). A disease similarity matrix based on the uniqueness of shared genes. BMC medical genomics, 1026. https://doi.org/10.1186/s12920-017-0265-2
Carson, Matthew B, et al. "A disease similarity matrix based on the uniqueness of shared genes." BMC medical genomics vol. 10 (2017): 26. doi: https://doi.org/10.1186/s12920-017-0265-2
Carson MB, Liu C, Lu Y, Jia C, Lu H. A disease similarity matrix based on the uniqueness of shared genes. BMC Med Genomics. 2017 May 24;10:26. doi: 10.1186/s12920-017-0265-2. PMID: 28589854; PMCID: PMC5461528.
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In-depth annotation of SNPs arising from resequencing projects using NGS-SNP.

Bioinformatics (Oxford, England)

Grant JR, Arantes AS, Liao X, Stothard P.
PMID: 21697123
Bioinformatics. 2011 Aug 15;27(16):2300-1. doi: 10.1093/bioinformatics/btr372. Epub 2011 Jun 22.

SUMMARY: NGS-SNP is a collection of command-line scripts for providing rich annotations for SNPs identified by the sequencing of whole genomes from any organism with reference sequences in Ensembl. Included among the annotations, several of which are not available...

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Grant JR, Arantes AS, Liao X, et al. In-depth annotation of SNPs arising from resequencing projects using NGS-SNP. Bioinformatics. 2011;27(16):2300-1doi: 10.1093/bioinformatics/btr372.
Grant, J. R., Arantes, A. S., Liao, X., & Stothard, P. (2011). In-depth annotation of SNPs arising from resequencing projects using NGS-SNP. Bioinformatics (Oxford, England), 27(16), 2300-1. https://doi.org/10.1093/bioinformatics/btr372
Grant, Jason R, et al. "In-depth annotation of SNPs arising from resequencing projects using NGS-SNP." Bioinformatics (Oxford, England) vol. 27,16 (2011): 2300-1. doi: https://doi.org/10.1093/bioinformatics/btr372
Grant JR, Arantes AS, Liao X, Stothard P. In-depth annotation of SNPs arising from resequencing projects using NGS-SNP. Bioinformatics. 2011 Aug 15;27(16):2300-1. doi: 10.1093/bioinformatics/btr372. Epub 2011 Jun 22. PMID: 21697123; PMCID: PMC3150039.
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Enabling enrichment analysis with the Human Disease Ontology.

Journal of biomedical informatics

LePendu P, Musen MA, Shah NH.
PMID: 21550421
J Biomed Inform. 2011 Dec;44:S31-S38. doi: 10.1016/j.jbi.2011.04.007. Epub 2011 Apr 29.

Advanced statistical methods used to analyze high-throughput data such as gene-expression assays result in long lists of "significant genes." One way to gain insight into the significance of altered expression levels is to determine whether Gene Ontology (GO) terms...

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LePendu P, Musen MA, Shah NH. Enabling enrichment analysis with the Human Disease Ontology. J Biomed Inform. 2011;44:S31-S38doi: 10.1016/j.jbi.2011.04.007.
LePendu, P., Musen, M. A., & Shah, N. H. (2011). Enabling enrichment analysis with the Human Disease Ontology. Journal of biomedical informatics, 44S31-S38. https://doi.org/10.1016/j.jbi.2011.04.007
LePendu, Paea, et al. "Enabling enrichment analysis with the Human Disease Ontology." Journal of biomedical informatics vol. 44 (2011): S31-S38. doi: https://doi.org/10.1016/j.jbi.2011.04.007
LePendu P, Musen MA, Shah NH. Enabling enrichment analysis with the Human Disease Ontology. J Biomed Inform. 2011 Dec;44:S31-S38. doi: 10.1016/j.jbi.2011.04.007. Epub 2011 Apr 29. PMID: 21550421; PMCID: PMC3392036.
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myKaryoView: a light-weight client for visualization of genomic data.

PloS one

Jimenez RC, Salazar GA, Gel B, Dopazo J, Mulder N, Corpas M.
PMID: 22046276
PLoS One. 2011;6(10):e26345. doi: 10.1371/journal.pone.0026345. Epub 2011 Oct 26.

The Distributed Annotation System (DAS) is a protocol for easy sharing and integration of biological annotations. In order to visualize feature annotations in a genomic context a client is required. Here we present myKaryoView, a simple light-weight DAS tool...

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Jimenez RC, Salazar GA, Gel B, et al. myKaryoView: a light-weight client for visualization of genomic data. PLoS One. 2011;6(10):e26345doi: 10.1371/journal.pone.0026345.
Jimenez, R. C., Salazar, G. A., Gel, B., Dopazo, J., Mulder, N., & Corpas, M. (2011). myKaryoView: a light-weight client for visualization of genomic data. PloS one, 6(10), e26345. https://doi.org/10.1371/journal.pone.0026345
Jimenez, Rafael C, et al. "myKaryoView: a light-weight client for visualization of genomic data." PloS one vol. 6,10 (2011): e26345. doi: https://doi.org/10.1371/journal.pone.0026345
Jimenez RC, Salazar GA, Gel B, Dopazo J, Mulder N, Corpas M. myKaryoView: a light-weight client for visualization of genomic data. PLoS One. 2011;6(10):e26345. doi: 10.1371/journal.pone.0026345. Epub 2011 Oct 26. PMID: 22046276; PMCID: PMC3202530.
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ParsEval: parallel comparison and analysis of gene structure annotations.

BMC bioinformatics

Standage DS, Brendel VP.
PMID: 22852583
BMC Bioinformatics. 2012 Aug 01;13:187. doi: 10.1186/1471-2105-13-187.

BACKGROUND: Accurate gene structure annotation is a fundamental but somewhat elusive goal of genome projects, as witnessed by the fact that (model) genomes typically undergo several cycles of re-annotation. In many cases, it is not only different versions of...

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Standage DS, Brendel VP. ParsEval: parallel comparison and analysis of gene structure annotations. BMC Bioinformatics. 2012;13:187doi: 10.1186/1471-2105-13-187.
Standage, D. S., & Brendel, V. P. (2012). ParsEval: parallel comparison and analysis of gene structure annotations. BMC bioinformatics, 13187. https://doi.org/10.1186/1471-2105-13-187
Standage, Daniel S, and Brendel, Volker P. "ParsEval: parallel comparison and analysis of gene structure annotations." BMC bioinformatics vol. 13 (2012): 187. doi: https://doi.org/10.1186/1471-2105-13-187
Standage DS, Brendel VP. ParsEval: parallel comparison and analysis of gene structure annotations. BMC Bioinformatics. 2012 Aug 01;13:187. doi: 10.1186/1471-2105-13-187. PMID: 22852583; PMCID: PMC3439248.
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MicrobesFlux: a web platform for drafting metabolic models from the KEGG database.

BMC systems biology

Feng X, Xu Y, Chen Y, Tang YJ.
PMID: 22857267
BMC Syst Biol. 2012 Aug 02;6:94. doi: 10.1186/1752-0509-6-94.

BACKGROUND: Concurrent with the efforts currently underway in mapping microbial genomes using high-throughput sequencing methods, systems biologists are building metabolic models to characterize and predict cell metabolisms. One of the key steps in building a metabolic model is using...

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Feng X, Xu Y, Chen Y, et al. MicrobesFlux: a web platform for drafting metabolic models from the KEGG database. BMC Syst Biol. 2012;6:94doi: 10.1186/1752-0509-6-94.
Feng, X., Xu, Y., Chen, Y., & Tang, Y. J. (2012). MicrobesFlux: a web platform for drafting metabolic models from the KEGG database. BMC systems biology, 694. https://doi.org/10.1186/1752-0509-6-94
Feng, Xueyang, et al. "MicrobesFlux: a web platform for drafting metabolic models from the KEGG database." BMC systems biology vol. 6 (2012): 94. doi: https://doi.org/10.1186/1752-0509-6-94
Feng X, Xu Y, Chen Y, Tang YJ. MicrobesFlux: a web platform for drafting metabolic models from the KEGG database. BMC Syst Biol. 2012 Aug 02;6:94. doi: 10.1186/1752-0509-6-94. PMID: 22857267; PMCID: PMC3447728.
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Sma3s: a three-step modular annotator for large sequence datasets.

DNA research : an international journal for rapid publication of reports on genes and genomes

Muñoz-Mérida A, Viguera E, Claros MG, Trelles O, Pérez-Pulido AJ.
PMID: 24501397
DNA Res. 2014 Aug;21(4):341-53. doi: 10.1093/dnares/dsu001. Epub 2014 Feb 05.

Automatic sequence annotation is an essential component of modern 'omics' studies, which aim to extract information from large collections of sequence data. Most existing tools use sequence homology to establish evolutionary relationships and assign putative functions to sequences. However,...

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Muñoz-Mérida A, Viguera E, Claros MG, et al. Sma3s: a three-step modular annotator for large sequence datasets. DNA Res. 2014;21(4):341-53doi: 10.1093/dnares/dsu001.
Muñoz-Mérida, A., Viguera, E., Claros, M. G., Trelles, O., & Pérez-Pulido, A. J. (2014). Sma3s: a three-step modular annotator for large sequence datasets. DNA research : an international journal for rapid publication of reports on genes and genomes, 21(4), 341-53. https://doi.org/10.1093/dnares/dsu001
Muñoz-Mérida, Antonio, et al. "Sma3s: a three-step modular annotator for large sequence datasets." DNA research : an international journal for rapid publication of reports on genes and genomes vol. 21,4 (2014): 341-53. doi: https://doi.org/10.1093/dnares/dsu001
Muñoz-Mérida A, Viguera E, Claros MG, Trelles O, Pérez-Pulido AJ. Sma3s: a three-step modular annotator for large sequence datasets. DNA Res. 2014 Aug;21(4):341-53. doi: 10.1093/dnares/dsu001. Epub 2014 Feb 05. PMID: 24501397; PMCID: PMC4131829.
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PloGO: plotting gene ontology annotation and abundance in multi-condition proteomics experiments.

Proteomics

Pascovici D, Keighley T, Mirzaei M, Haynes PA, Cooke B.
PMID: 22213732
Proteomics. 2012 Feb;12(3):406-10. doi: 10.1002/pmic.201100445. Epub 2012 Jan 18.

We describe the PloGO R package, a simple open-source tool for plotting gene ontology (GO) annotation and abundance information, which was developed to aid with the bioinformatics analysis of multi-condition label-free proteomics experiments using quantitation based on spectral counting....

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Pascovici D, Keighley T, Mirzaei M, et al. PloGO: plotting gene ontology annotation and abundance in multi-condition proteomics experiments. Proteomics. 2012;12(3):406-10doi: 10.1002/pmic.201100445.
Pascovici, D., Keighley, T., Mirzaei, M., Haynes, P. A., & Cooke, B. (2012). PloGO: plotting gene ontology annotation and abundance in multi-condition proteomics experiments. Proteomics, 12(3), 406-10. https://doi.org/10.1002/pmic.201100445
Pascovici, Dana, et al. "PloGO: plotting gene ontology annotation and abundance in multi-condition proteomics experiments." Proteomics vol. 12,3 (2012): 406-10. doi: https://doi.org/10.1002/pmic.201100445
Pascovici D, Keighley T, Mirzaei M, Haynes PA, Cooke B. PloGO: plotting gene ontology annotation and abundance in multi-condition proteomics experiments. Proteomics. 2012 Feb;12(3):406-10. doi: 10.1002/pmic.201100445. Epub 2012 Jan 18. PMID: 22213732.
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AutismKB 2.0: a knowledgebase for the genetic evidence of autism spectrum disorder.

Database : the journal of biological databases and curation

Yang C, Li J, Wu Q, Yang X, Huang AY, Zhang J, Ye AY, Dou Y, Yan L, Zhou WZ, Kong L, Wang M, Ai C, Yang D, Wei L.
PMID: 30339214
Database (Oxford). 2018 Jan 01;2018. doi: 10.1093/database/bay106.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with strong genetic contributions. To provide a comprehensive resource for the genetic evidence of ASD, we have updated the Autism KnowledgeBase (AutismKB) to version 2.0. AutismKB 2.0 integrates multiscale genetic...

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Yang C, Li J, Wu Q, et al. AutismKB 2.0: a knowledgebase for the genetic evidence of autism spectrum disorder. Database (Oxford). 2018;2018doi: 10.1093/database/bay106.
Yang, C., Li, J., Wu, Q., Yang, X., Huang, A. Y., Zhang, J., Ye, A. Y., Dou, Y., Yan, L., Zhou, W. Z., Kong, L., Wang, M., Ai, C., Yang, D., & Wei, L. (2018). AutismKB 2.0: a knowledgebase for the genetic evidence of autism spectrum disorder. Database : the journal of biological databases and curation, 2018. https://doi.org/10.1093/database/bay106
Yang, Changhong, et al. "AutismKB 2.0: a knowledgebase for the genetic evidence of autism spectrum disorder." Database : the journal of biological databases and curation vol. 2018 (2018). doi: https://doi.org/10.1093/database/bay106
Yang C, Li J, Wu Q, Yang X, Huang AY, Zhang J, Ye AY, Dou Y, Yan L, Zhou WZ, Kong L, Wang M, Ai C, Yang D, Wei L. AutismKB 2.0: a knowledgebase for the genetic evidence of autism spectrum disorder. Database (Oxford). 2018 Jan 01;2018. doi: 10.1093/database/bay106. PMID: 30339214; PMCID: PMC6193446.
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GO FEAT: a rapid web-based functional annotation tool for genomic and transcriptomic data.

Scientific reports

Araujo FA, Barh D, Silva A, Guimarães L, Ramos RTJ.
PMID: 29379090
Sci Rep. 2018 Jan 29;8(1):1794. doi: 10.1038/s41598-018-20211-9.

Downstream analysis of genomic and transcriptomic sequence data is often executed by functional annotation that can be performed by various bioinformatics tools and biological databases. However, a full fast integrated tool is not available for such analysis. Besides, the...

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Araujo FA, Barh D, Silva A, et al. GO FEAT: a rapid web-based functional annotation tool for genomic and transcriptomic data. Sci Rep. 2018;8(1):1794doi: 10.1038/s41598-018-20211-9.
Araujo, F. A., Barh, D., Silva, A., Guimarães, L., & Ramos, R. T. J. (2018). GO FEAT: a rapid web-based functional annotation tool for genomic and transcriptomic data. Scientific reports, 8(1), 1794. https://doi.org/10.1038/s41598-018-20211-9
Araujo, Fabricio Almeida, et al. "GO FEAT: a rapid web-based functional annotation tool for genomic and transcriptomic data." Scientific reports vol. 8,1 (2018): 1794. doi: https://doi.org/10.1038/s41598-018-20211-9
Araujo FA, Barh D, Silva A, Guimarães L, Ramos RTJ. GO FEAT: a rapid web-based functional annotation tool for genomic and transcriptomic data. Sci Rep. 2018 Jan 29;8(1):1794. doi: 10.1038/s41598-018-20211-9. PMID: 29379090; PMCID: PMC5789007.
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Showing 1 to 12 of 109 entries