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Showing 13 to 24 of 109 entries
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WEGO 2.0: a web tool for analyzing and plotting GO annotations, 2018 update.

Nucleic acids research

Ye J, Zhang Y, Cui H, Liu J, Wu Y, Cheng Y, Xu H, Huang X, Li S, Zhou A, Zhang X, Bolund L, Chen Q, Wang J, Yang H, Fang L, Shi C.
PMID: 29788377
Nucleic Acids Res. 2018 Jul 02;46:W71-W75. doi: 10.1093/nar/gky400.

WEGO (Web Gene Ontology Annotation Plot), created in 2006, is a simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results. Owing largely to the rapid development of high-throughput sequencing and the increasing acceptance of...

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Ye J, Zhang Y, Cui H, et al. WEGO 2.0: a web tool for analyzing and plotting GO annotations, 2018 update. Nucleic Acids Res. 2018;46:W71-W75doi: 10.1093/nar/gky400.
Ye, J., Zhang, Y., Cui, H., Liu, J., Wu, Y., Cheng, Y., Xu, H., Huang, X., Li, S., Zhou, A., Zhang, X., Bolund, L., Chen, Q., Wang, J., Yang, H., Fang, L., & Shi, C. (2018). WEGO 2.0: a web tool for analyzing and plotting GO annotations, 2018 update. Nucleic acids research, 46W71-W75. https://doi.org/10.1093/nar/gky400
Ye, Jia, et al. "WEGO 2.0: a web tool for analyzing and plotting GO annotations, 2018 update." Nucleic acids research vol. 46 (2018): W71-W75. doi: https://doi.org/10.1093/nar/gky400
Ye J, Zhang Y, Cui H, Liu J, Wu Y, Cheng Y, Xu H, Huang X, Li S, Zhou A, Zhang X, Bolund L, Chen Q, Wang J, Yang H, Fang L, Shi C. WEGO 2.0: a web tool for analyzing and plotting GO annotations, 2018 update. Nucleic Acids Res. 2018 Jul 02;46:W71-W75. doi: 10.1093/nar/gky400. PMID: 29788377; PMCID: PMC6030983.
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Computational prediction of functions of intrinsically disordered regions.

Progress in molecular biology and translational science

Katuwawala A, Ghadermarzi S, Kurgan L.
PMID: 31521235
Prog Mol Biol Transl Sci. 2019;166:341-369. doi: 10.1016/bs.pmbts.2019.04.006. Epub 2019 May 20.

Intrinsically disorder regions (IDRs) are abundant in nature, particularly among Eukaryotes. While they facilitate a wide spectrum of cellular functions including signaling, molecular assembly and recognition, translation, transcription and regulation, only several hundred IDRs are annotated functionally. This annotation...

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Katuwawala A, Ghadermarzi S, Kurgan L. Computational prediction of functions of intrinsically disordered regions. Prog Mol Biol Transl Sci. 2019;166:341-369doi: 10.1016/bs.pmbts.2019.04.006.
Katuwawala, A., Ghadermarzi, S., & Kurgan, L. (2019). Computational prediction of functions of intrinsically disordered regions. Progress in molecular biology and translational science, 166341-369. https://doi.org/10.1016/bs.pmbts.2019.04.006
Katuwawala, Akila, et al. "Computational prediction of functions of intrinsically disordered regions." Progress in molecular biology and translational science vol. 166 (2019): 341-369. doi: https://doi.org/10.1016/bs.pmbts.2019.04.006
Katuwawala A, Ghadermarzi S, Kurgan L. Computational prediction of functions of intrinsically disordered regions. Prog Mol Biol Transl Sci. 2019;166:341-369. doi: 10.1016/bs.pmbts.2019.04.006. Epub 2019 May 20. PMID: 31521235.
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UniProt: a worldwide hub of protein knowledge.

Nucleic acids research

[No authors listed]
PMID: 30395287
Nucleic Acids Res. 2019 Jan 08;47:D506-D515. doi: 10.1093/nar/gky1049.

The UniProt Knowledgebase is a collection of sequences and annotations for over 120 million proteins across all branches of life. Detailed annotations extracted from the literature by expert curators have been collected for over half a million of these...

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UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res. 2019;47:D506-D515doi: 10.1093/nar/gky1049.
(2019). UniProt: a worldwide hub of protein knowledge. Nucleic acids research, 47D506-D515. https://doi.org/10.1093/nar/gky1049
"UniProt: a worldwide hub of protein knowledge." Nucleic acids research vol. 47 (2019): D506-D515. doi: https://doi.org/10.1093/nar/gky1049
UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res. 2019 Jan 08;47:D506-D515. doi: 10.1093/nar/gky1049. PMID: 30395287; PMCID: PMC6323992.
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Integration of small RNAs and transcriptome sequencing uncovers a complex regulatory network during vernalization and heading stages of orchardgrass (Dactylis glomerata L.).

BMC genomics

Feng G, Xu L, Wang J, Nie G, Bushman BS, Xie W, Yan H, Yang Z, Guan H, Huang L, Zhang X.
PMID: 30285619
BMC Genomics. 2018 Oct 03;19(1):727. doi: 10.1186/s12864-018-5104-0.

BACKGROUND: Flowering is a critical reproductive process in higher plants. Timing of optimal flowering depends upon the coordination among seasonal environmental cues. For cool season grasses, such as Dactylis glomerata, vernalization induced by low temperature provides competence to initiate...

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Feng G, Xu L, Wang J, et al. Integration of small RNAs and transcriptome sequencing uncovers a complex regulatory network during vernalization and heading stages of orchardgrass (Dactylis glomerata L.). BMC Genomics. 2018;19(1):727doi: 10.1186/s12864-018-5104-0.
Feng, G., Xu, L., Wang, J., Nie, G., Bushman, B. S., Xie, W., Yan, H., Yang, Z., Guan, H., Huang, L., & Zhang, X. (2018). Integration of small RNAs and transcriptome sequencing uncovers a complex regulatory network during vernalization and heading stages of orchardgrass (Dactylis glomerata L.). BMC genomics, 19(1), 727. https://doi.org/10.1186/s12864-018-5104-0
Feng, Guangyan, et al. "Integration of small RNAs and transcriptome sequencing uncovers a complex regulatory network during vernalization and heading stages of orchardgrass (Dactylis glomerata L.)." BMC genomics vol. 19,1 (2018): 727. doi: https://doi.org/10.1186/s12864-018-5104-0
Feng G, Xu L, Wang J, Nie G, Bushman BS, Xie W, Yan H, Yang Z, Guan H, Huang L, Zhang X. Integration of small RNAs and transcriptome sequencing uncovers a complex regulatory network during vernalization and heading stages of orchardgrass (Dactylis glomerata L.). BMC Genomics. 2018 Oct 03;19(1):727. doi: 10.1186/s12864-018-5104-0. PMID: 30285619; PMCID: PMC6171228.
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Genome Annotation Generator: a simple tool for generating and correcting WGS annotation tables for NCBI submission.

GigaScience

Geib SM, Hall B, Derego T, Bremer FT, Cannoles K, Sim SB.
PMID: 29635297
Gigascience. 2018 Apr 01;7(4):1-5. doi: 10.1093/gigascience/giy018.

BACKGROUND: One of the most overlooked, yet critical, components of a whole genome sequencing (WGS) project is the submission and curation of the data to a genomic repository, most commonly the National Center for Biotechnology Information (NCBI). While large...

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Geib SM, Hall B, Derego T, et al. Genome Annotation Generator: a simple tool for generating and correcting WGS annotation tables for NCBI submission. Gigascience. 2018;7(4):1-5doi: 10.1093/gigascience/giy018.
Geib, S. M., Hall, B., Derego, T., Bremer, F. T., Cannoles, K., & Sim, S. B. (2018). Genome Annotation Generator: a simple tool for generating and correcting WGS annotation tables for NCBI submission. GigaScience, 7(4), 1-5. https://doi.org/10.1093/gigascience/giy018
Geib, Scott M, et al. "Genome Annotation Generator: a simple tool for generating and correcting WGS annotation tables for NCBI submission." GigaScience vol. 7,4 (2018): 1-5. doi: https://doi.org/10.1093/gigascience/giy018
Geib SM, Hall B, Derego T, Bremer FT, Cannoles K, Sim SB. Genome Annotation Generator: a simple tool for generating and correcting WGS annotation tables for NCBI submission. Gigascience. 2018 Apr 01;7(4):1-5. doi: 10.1093/gigascience/giy018. PMID: 29635297; PMCID: PMC5887294.
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Directly e-mailing authors of newly published papers encourages community curation.

Database : the journal of biological databases and curation

Bunt SM, Grumbling GB, Field HI, Marygold SJ, Brown NH, Millburn GH.
PMID: 22554788
Database (Oxford). 2012 May 02;2012:bas024. doi: 10.1093/database/bas024. Print 2012.

Much of the data within Model Organism Databases (MODs) comes from manual curation of the primary research literature. Given limited funding and an increasing density of published material, a significant challenge facing all MODs is how to efficiently and...

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Bunt SM, Grumbling GB, Field HI, et al. Directly e-mailing authors of newly published papers encourages community curation. Database (Oxford). 2012;2012:bas024doi: 10.1093/database/bas024.
Bunt, S. M., Grumbling, G. B., Field, H. I., Marygold, S. J., Brown, N. H., Millburn, G. H. (2012). Directly e-mailing authors of newly published papers encourages community curation. Database : the journal of biological databases and curation, 2012bas024. https://doi.org/10.1093/database/bas024
Bunt, Stephanie M, et al. "Directly e-mailing authors of newly published papers encourages community curation." Database : the journal of biological databases and curation vol. 2012 (2012): bas024. doi: https://doi.org/10.1093/database/bas024
Bunt SM, Grumbling GB, Field HI, Marygold SJ, Brown NH, Millburn GH. Directly e-mailing authors of newly published papers encourages community curation. Database (Oxford). 2012 May 02;2012:bas024. doi: 10.1093/database/bas024. Print 2012. PMID: 22554788; PMCID: PMC3342516.
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Annotare--a tool for annotating high-throughput biomedical investigations and resulting data.

Bioinformatics (Oxford, England)

Shankar R, Parkinson H, Burdett T, Hastings E, Liu J, Miller M, Srinivasa R, White J, Brazma A, Sherlock G, Stoeckert CJ, Ball CA.
PMID: 20733062
Bioinformatics. 2010 Oct 01;26(19):2470-1. doi: 10.1093/bioinformatics/btq462. Epub 2010 Aug 23.

UNLABELLED: Computational methods in molecular biology will increasingly depend on standards-based annotations that describe biological experiments in an unambiguous manner. Annotare is a software tool that enables biologists to easily annotate their high-throughput experiments, biomaterials and data in a...

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Shankar R, Parkinson H, Burdett T, et al. Annotare--a tool for annotating high-throughput biomedical investigations and resulting data. Bioinformatics. 2010;26(19):2470-1doi: 10.1093/bioinformatics/btq462.
Shankar, R., Parkinson, H., Burdett, T., Hastings, E., Liu, J., Miller, M., Srinivasa, R., White, J., Brazma, A., Sherlock, G., Stoeckert, C. J., & Ball, C. A. (2010). Annotare--a tool for annotating high-throughput biomedical investigations and resulting data. Bioinformatics (Oxford, England), 26(19), 2470-1. https://doi.org/10.1093/bioinformatics/btq462
Shankar, Ravi, et al. "Annotare--a tool for annotating high-throughput biomedical investigations and resulting data." Bioinformatics (Oxford, England) vol. 26,19 (2010): 2470-1. doi: https://doi.org/10.1093/bioinformatics/btq462
Shankar R, Parkinson H, Burdett T, Hastings E, Liu J, Miller M, Srinivasa R, White J, Brazma A, Sherlock G, Stoeckert CJ, Ball CA. Annotare--a tool for annotating high-throughput biomedical investigations and resulting data. Bioinformatics. 2010 Oct 01;26(19):2470-1. doi: 10.1093/bioinformatics/btq462. Epub 2010 Aug 23. PMID: 20733062; PMCID: PMC2944206.
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RefMet: a reference nomenclature for metabolomics.

Nature methods

Fahy E, Subramaniam S.
PMID: 33199890
Nat Methods. 2020 Dec;17(12):1173-1174. doi: 10.1038/s41592-020-01009-y.

No abstract available.

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Fahy E, Subramaniam S. RefMet: a reference nomenclature for metabolomics. Nat Methods. 2020;17(12):1173-1174doi: 10.1038/s41592-020-01009-y.
Fahy, E., & Subramaniam, S. (2020). RefMet: a reference nomenclature for metabolomics. Nature methods, 17(12), 1173-1174. https://doi.org/10.1038/s41592-020-01009-y
Fahy, Eoin, and Subramaniam, Shankar. "RefMet: a reference nomenclature for metabolomics." Nature methods vol. 17,12 (2020): 1173-1174. doi: https://doi.org/10.1038/s41592-020-01009-y
Fahy E, Subramaniam S. RefMet: a reference nomenclature for metabolomics. Nat Methods. 2020 Dec;17(12):1173-1174. doi: 10.1038/s41592-020-01009-y. PMID: 33199890.
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VarFish: comprehensive DNA variant analysis for diagnostics and research.

Nucleic acids research

Holtgrewe M, Stolpe O, Nieminen M, Mundlos S, Knaus A, Kornak U, Seelow D, Segebrecht L, Spielmann M, Fischer-Zirnsak B, Boschann F, Scholl U, Ehmke N, Beule D.
PMID: 32338743
Nucleic Acids Res. 2020 Jul 02;48:W162-W169. doi: 10.1093/nar/gkaa241.

VarFish is a user-friendly web application for the quality control, filtering, prioritization, analysis, and user-based annotation of DNA variant data with a focus on rare disease genetics. It is capable of processing variant call files with single or multiple...

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Holtgrewe M, Stolpe O, Nieminen M, et al. VarFish: comprehensive DNA variant analysis for diagnostics and research. Nucleic Acids Res. 2020;48:W162-W169doi: 10.1093/nar/gkaa241.
Holtgrewe, M., Stolpe, O., Nieminen, M., Mundlos, S., Knaus, A., Kornak, U., Seelow, D., Segebrecht, L., Spielmann, M., Fischer-Zirnsak, B., Boschann, F., Scholl, U., Ehmke, N., & Beule, D. (2020). VarFish: comprehensive DNA variant analysis for diagnostics and research. Nucleic acids research, 48W162-W169. https://doi.org/10.1093/nar/gkaa241
Holtgrewe, Manuel, et al. "VarFish: comprehensive DNA variant analysis for diagnostics and research." Nucleic acids research vol. 48 (2020): W162-W169. doi: https://doi.org/10.1093/nar/gkaa241
Holtgrewe M, Stolpe O, Nieminen M, Mundlos S, Knaus A, Kornak U, Seelow D, Segebrecht L, Spielmann M, Fischer-Zirnsak B, Boschann F, Scholl U, Ehmke N, Beule D. VarFish: comprehensive DNA variant analysis for diagnostics and research. Nucleic Acids Res. 2020 Jul 02;48:W162-W169. doi: 10.1093/nar/gkaa241. PMID: 32338743; PMCID: PMC7319464.
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Gene Annotation Easy Viewer (GAEV): Integrating KEGG's Gene Function Annotations and Associated Molecular Pathways.

F1000Research

Huynh T, Xu S.
PMID: 30705748
F1000Res. 2018 Mar 29;7:416. doi: 10.12688/f1000research.14012.3. eCollection 2018.

We developed a Gene Annotation Easy Viewer (GAEV) that integrates the gene annotation data from the KEGG (Kyoto Encyclopedia of Genes and Genomes) Automatic Annotation Server. GAEV generates an easy-to-read table that summarizes the query gene name, the KO...

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Huynh T, Xu S. Gene Annotation Easy Viewer (GAEV): Integrating KEGG's Gene Function Annotations and Associated Molecular Pathways. F1000Res. 2018;7:416doi: 10.12688/f1000research.14012.3.
Huynh, T., & Xu, S. (2018). Gene Annotation Easy Viewer (GAEV): Integrating KEGG's Gene Function Annotations and Associated Molecular Pathways. F1000Research, 7416. https://doi.org/10.12688/f1000research.14012.3
Huynh, Trung, and Xu, Sen. "Gene Annotation Easy Viewer (GAEV): Integrating KEGG's Gene Function Annotations and Associated Molecular Pathways." F1000Research vol. 7 (2018): 416. doi: https://doi.org/10.12688/f1000research.14012.3
Huynh T, Xu S. Gene Annotation Easy Viewer (GAEV): Integrating KEGG's Gene Function Annotations and Associated Molecular Pathways. F1000Res. 2018 Mar 29;7:416. doi: 10.12688/f1000research.14012.3. eCollection 2018. PMID: 30705748; PMCID: PMC6343226.
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An integrative methodology based on protein-protein interaction networks for identification and functional annotation of disease-relevant genes applied to channelopathies.

BMC bioinformatics

Marín M, Esteban FJ, Ramírez-Rodrigo H, Ros E, Sáez-Lara MJ.
PMID: 31718537
BMC Bioinformatics. 2019 Nov 12;20(1):565. doi: 10.1186/s12859-019-3162-1.

BACKGROUND: Biologically data-driven networks have become powerful analytical tools that handle massive, heterogeneous datasets generated from biomedical fields. Protein-protein interaction networks can identify the most relevant structures directly tied to biological functions. Functional enrichments can then be performed based...

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Marín M, Esteban FJ, Ramírez-Rodrigo H, et al. An integrative methodology based on protein-protein interaction networks for identification and functional annotation of disease-relevant genes applied to channelopathies. BMC Bioinformatics. 2019;20(1):565doi: 10.1186/s12859-019-3162-1.
Marín, M., Esteban, F. J., Ramírez-Rodrigo, H., Ros, E., & Sáez-Lara, M. J. (2019). An integrative methodology based on protein-protein interaction networks for identification and functional annotation of disease-relevant genes applied to channelopathies. BMC bioinformatics, 20(1), 565. https://doi.org/10.1186/s12859-019-3162-1
Marín, Milagros, et al. "An integrative methodology based on protein-protein interaction networks for identification and functional annotation of disease-relevant genes applied to channelopathies." BMC bioinformatics vol. 20,1 (2019): 565. doi: https://doi.org/10.1186/s12859-019-3162-1
Marín M, Esteban FJ, Ramírez-Rodrigo H, Ros E, Sáez-Lara MJ. An integrative methodology based on protein-protein interaction networks for identification and functional annotation of disease-relevant genes applied to channelopathies. BMC Bioinformatics. 2019 Nov 12;20(1):565. doi: 10.1186/s12859-019-3162-1. PMID: 31718537; PMCID: PMC6849233.
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Leveraging functional annotation to identify genes associated with complex diseases.

PLoS computational biology

Liu W, Li M, Zhang W, Zhou G, Wu X, Wang J, Lu Q, Zhao H.
PMID: 33137096
PLoS Comput Biol. 2020 Nov 02;16(11):e1008315. doi: 10.1371/journal.pcbi.1008315. eCollection 2020 Nov.

To increase statistical power to identify genes associated with complex traits, a number of transcriptome-wide association study (TWAS) methods have been proposed using gene expression as a mediating trait linking genetic variations and diseases. These methods first predict expression...

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Liu W, Li M, Zhang W, et al. Leveraging functional annotation to identify genes associated with complex diseases. PLoS Comput Biol. 2020;16(11):e1008315doi: 10.1371/journal.pcbi.1008315.
Liu, W., Li, M., Zhang, W., Zhou, G., Wu, X., Wang, J., Lu, Q., & Zhao, H. (2020). Leveraging functional annotation to identify genes associated with complex diseases. PLoS computational biology, 16(11), e1008315. https://doi.org/10.1371/journal.pcbi.1008315
Liu, Wei, et al. "Leveraging functional annotation to identify genes associated with complex diseases." PLoS computational biology vol. 16,11 (2020): e1008315. doi: https://doi.org/10.1371/journal.pcbi.1008315
Liu W, Li M, Zhang W, Zhou G, Wu X, Wang J, Lu Q, Zhao H. Leveraging functional annotation to identify genes associated with complex diseases. PLoS Comput Biol. 2020 Nov 02;16(11):e1008315. doi: 10.1371/journal.pcbi.1008315. eCollection 2020 Nov. PMID: 33137096; PMCID: PMC7660930.
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Showing 13 to 24 of 109 entries