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Showing 1 to 12 of 15 entries
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Protein technologies.

Current opinion in biotechnology

Timms JF.
PMID: 18678249
Curr Opin Biotechnol. 2008 Aug;19(4):313-5. doi: 10.1016/j.copbio.2008.07.003. Epub 2008 Aug 11.

No abstract available.

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Timms JF. Protein technologies. Curr Opin Biotechnol. 2008;19(4):313-5doi: 10.1016/j.copbio.2008.07.003.
Timms, J. F. (2008). Protein technologies. Current opinion in biotechnology, 19(4), 313-5. https://doi.org/10.1016/j.copbio.2008.07.003
Timms, John F. "Protein technologies." Current opinion in biotechnology vol. 19,4 (2008): 313-5. doi: https://doi.org/10.1016/j.copbio.2008.07.003
Timms JF. Protein technologies. Curr Opin Biotechnol. 2008 Aug;19(4):313-5. doi: 10.1016/j.copbio.2008.07.003. Epub 2008 Aug 11. PMID: 18678249.
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Towards a human proteomics atlas.

Analytical and bioanalytical chemistry

Gonnelli G, Hulstaert N, Degroeve S, Martens L.
PMID: 22447219
Anal Bioanal Chem. 2012 Sep;404(4):1069-77. doi: 10.1007/s00216-012-5940-8. Epub 2012 Mar 25.

Proteomics research has taken up an increasingly important role in life sciences over the past few years. Due to a strong push from publishers and funders alike, the community has also started to freely share its data in earnest,...

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Gonnelli G, Hulstaert N, Degroeve S, et al. Towards a human proteomics atlas. Anal Bioanal Chem. 2012;404(4):1069-77doi: 10.1007/s00216-012-5940-8.
Gonnelli, G., Hulstaert, N., Degroeve, S., & Martens, L. (2012). Towards a human proteomics atlas. Analytical and bioanalytical chemistry, 404(4), 1069-77. https://doi.org/10.1007/s00216-012-5940-8
Gonnelli, Giulia, et al. "Towards a human proteomics atlas." Analytical and bioanalytical chemistry vol. 404,4 (2012): 1069-77. doi: https://doi.org/10.1007/s00216-012-5940-8
Gonnelli G, Hulstaert N, Degroeve S, Martens L. Towards a human proteomics atlas. Anal Bioanal Chem. 2012 Sep;404(4):1069-77. doi: 10.1007/s00216-012-5940-8. Epub 2012 Mar 25. PMID: 22447219.
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Protein-protein interactions prediction based on iterative clique extension with gene ontology filtering.

TheScientificWorldJournal

Yang L, Tang X.
PMID: 24578640
ScientificWorldJournal. 2014 Jan 22;2014:523634. doi: 10.1155/2014/523634. eCollection 2014.

Cliques (maximal complete subnets) in protein-protein interaction (PPI) network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend...

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Yang L, Tang X. Protein-protein interactions prediction based on iterative clique extension with gene ontology filtering. ScientificWorldJournal. 2014;2014:523634doi: 10.1155/2014/523634.
Yang, L., & Tang, X. (2014). Protein-protein interactions prediction based on iterative clique extension with gene ontology filtering. TheScientificWorldJournal, 2014523634. https://doi.org/10.1155/2014/523634
Yang, Lei, and Tang, Xianglong. "Protein-protein interactions prediction based on iterative clique extension with gene ontology filtering." TheScientificWorldJournal vol. 2014 (2014): 523634. doi: https://doi.org/10.1155/2014/523634
Yang L, Tang X. Protein-protein interactions prediction based on iterative clique extension with gene ontology filtering. ScientificWorldJournal. 2014 Jan 22;2014:523634. doi: 10.1155/2014/523634. eCollection 2014. PMID: 24578640; PMCID: PMC3919085.
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Expectations from structural genomics revisited: an analysis of structural genomics targets.

American journal of pharmacogenomics : genomics-related research in drug development and clinical practice

Saqi MA, Wild DL.
PMID: 16196503
Am J Pharmacogenomics. 2005;5(5):339-42. doi: 10.2165/00129785-200505050-00006.

BACKGROUND: Current structural genomics projects are being driven by two main goals; to produce a representative set of protein folds that could be used as templates for comparative modeling purposes, and to provide insight into the function of the...

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Saqi MA, Wild DL. Expectations from structural genomics revisited: an analysis of structural genomics targets. Am J Pharmacogenomics. 2005;5(5):339-42doi: 10.2165/00129785-200505050-00006.
Saqi, M. A., & Wild, D. L. (2005). Expectations from structural genomics revisited: an analysis of structural genomics targets. American journal of pharmacogenomics : genomics-related research in drug development and clinical practice, 5(5), 339-42. https://doi.org/10.2165/00129785-200505050-00006
Saqi, Mansoor A S, and Wild, David L. "Expectations from structural genomics revisited: an analysis of structural genomics targets." American journal of pharmacogenomics : genomics-related research in drug development and clinical practice vol. 5,5 (2005): 339-42. doi: https://doi.org/10.2165/00129785-200505050-00006
Saqi MA, Wild DL. Expectations from structural genomics revisited: an analysis of structural genomics targets. Am J Pharmacogenomics. 2005;5(5):339-42. doi: 10.2165/00129785-200505050-00006. PMID: 16196503.
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UniHI 4: new tools for query, analysis and visualization of the human protein-protein interactome.

Nucleic acids research

Chaurasia G, Malhotra S, Russ J, Schnoegl S, Hänig C, Wanker EE, Futschik ME.
PMID: 18984619
Nucleic Acids Res. 2009 Jan;37:D657-60. doi: 10.1093/nar/gkn841. Epub 2008 Nov 04.

Human protein interaction maps have become important tools of biomedical research for the elucidation of molecular mechanisms and the identification of new modulators of disease processes. The Unified Human Interactome database (UniHI, http://www.unihi.org) provides researchers with a comprehensive platform...

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Chaurasia G, Malhotra S, Russ J, et al. UniHI 4: new tools for query, analysis and visualization of the human protein-protein interactome. Nucleic Acids Res. 2008;37:D657-60doi: 10.1093/nar/gkn841.
Chaurasia, G., Malhotra, S., Russ, J., Schnoegl, S., Hänig, C., Wanker, E. E., & Futschik, M. E. (2009). UniHI 4: new tools for query, analysis and visualization of the human protein-protein interactome. Nucleic acids research, 37D657-60. https://doi.org/10.1093/nar/gkn841
Chaurasia, Gautam, et al. "UniHI 4: new tools for query, analysis and visualization of the human protein-protein interactome." Nucleic acids research vol. 37 (2009): D657-60. doi: https://doi.org/10.1093/nar/gkn841
Chaurasia G, Malhotra S, Russ J, Schnoegl S, Hänig C, Wanker EE, Futschik ME. UniHI 4: new tools for query, analysis and visualization of the human protein-protein interactome. Nucleic Acids Res. 2009 Jan;37:D657-60. doi: 10.1093/nar/gkn841. Epub 2008 Nov 04. PMID: 18984619; PMCID: PMC2686569.
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Bioinformatics tools for the functional interpretation of quantitative proteomics results.

Current topics in medicinal chemistry

Villavicencio-Diaz TN, Rodriguez-Ulloa A, Guirola-Cruz O, Perez-Riverol Y.
PMID: 24304321
Curr Top Med Chem. 2014;14(3):435-49. doi: 10.2174/1568026613666131204105110.

Proteins are the principal mediators of the functions in the cell; therefore, any abnormal variations on their abundance levels may reflect the presence of pathological processes. In this sense, many researchers rely on the functional interpretation of protein lists...

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Villavicencio-Diaz TN, Rodriguez-Ulloa A, Guirola-Cruz O, et al. Bioinformatics tools for the functional interpretation of quantitative proteomics results. Curr Top Med Chem. 2014;14(3):435-49doi: 10.2174/1568026613666131204105110.
Villavicencio-Diaz, T. N., Rodriguez-Ulloa, A., Guirola-Cruz, O., & Perez-Riverol, Y. (2014). Bioinformatics tools for the functional interpretation of quantitative proteomics results. Current topics in medicinal chemistry, 14(3), 435-49. https://doi.org/10.2174/1568026613666131204105110
Villavicencio-Diaz, Teresa Nunez, et al. "Bioinformatics tools for the functional interpretation of quantitative proteomics results." Current topics in medicinal chemistry vol. 14,3 (2014): 435-49. doi: https://doi.org/10.2174/1568026613666131204105110
Villavicencio-Diaz TN, Rodriguez-Ulloa A, Guirola-Cruz O, Perez-Riverol Y. Bioinformatics tools for the functional interpretation of quantitative proteomics results. Curr Top Med Chem. 2014;14(3):435-49. doi: 10.2174/1568026613666131204105110. PMID: 24304321.
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Prediction of a missing protein expression map in the context of the human proteome project.

Journal of proteome research

Guruceaga E, Sanchez del Pino MM, Corrales FJ, Segura V.
PMID: 25612097
J Proteome Res. 2015 Mar 06;14(3):1350-60. doi: 10.1021/pr500850u. Epub 2015 Feb 05.

Experimental evidence for the entire human proteome has been defined in the Human Proteome Project, and it is publicly available in the neXtProt database. However, there are still human proteins for which reliable experimental evidence does not exist, and...

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Guruceaga E, Sanchez del Pino MM, Corrales FJ, et al. Prediction of a missing protein expression map in the context of the human proteome project. J Proteome Res. 2015;14(3):1350-60doi: 10.1021/pr500850u.
Guruceaga, E., Sanchez del Pino, M. M., Corrales, F. J., & Segura, V. (2015). Prediction of a missing protein expression map in the context of the human proteome project. Journal of proteome research, 14(3), 1350-60. https://doi.org/10.1021/pr500850u
Guruceaga, Elizabeth, et al. "Prediction of a missing protein expression map in the context of the human proteome project." Journal of proteome research vol. 14,3 (2015): 1350-60. doi: https://doi.org/10.1021/pr500850u
Guruceaga E, Sanchez del Pino MM, Corrales FJ, Segura V. Prediction of a missing protein expression map in the context of the human proteome project. J Proteome Res. 2015 Mar 06;14(3):1350-60. doi: 10.1021/pr500850u. Epub 2015 Feb 05. PMID: 25612097.
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What history tells us XXXVIII. Resurrection of a transient forgotten model of gene action.

Journal of biosciences

Morange M.
PMID: 26333393
J Biosci. 2015 Sep;40(3):473-6. doi: 10.1007/s12038-015-9539-z.

No abstract available.

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Morange M. What history tells us XXXVIII. Resurrection of a transient forgotten model of gene action. J Biosci. 2015;40(3):473-6doi: 10.1007/s12038-015-9539-z.
Morange, M. (2015). What history tells us XXXVIII. Resurrection of a transient forgotten model of gene action. Journal of biosciences, 40(3), 473-6. https://doi.org/10.1007/s12038-015-9539-z
Morange, Michel. "What history tells us XXXVIII. Resurrection of a transient forgotten model of gene action." Journal of biosciences vol. 40,3 (2015): 473-6. doi: https://doi.org/10.1007/s12038-015-9539-z
Morange M. What history tells us XXXVIII. Resurrection of a transient forgotten model of gene action. J Biosci. 2015 Sep;40(3):473-6. doi: 10.1007/s12038-015-9539-z. PMID: 26333393.
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NetSets.js: a JavaScript framework for compositional assessment and comparison of biological networks through Venn-integrated network diagrams.

Bioinformatics (Oxford, England)

Nagpal S, Kuntal BK, Mande SS.
PMID: 32805035
Bioinformatics. 2021 May 01;37(4):580-582. doi: 10.1093/bioinformatics/btaa723.

MOTIVATION: Venn diagrams are frequently used to compare composition of datasets (e.g. datasets containing list of proteins and genes). Network diagram constructed using such datasets are usually generated using 'list of edges', popularly known as edge-lists. An edge-list and...

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Nagpal S, Kuntal BK, Mande SS. NetSets.js: a JavaScript framework for compositional assessment and comparison of biological networks through Venn-integrated network diagrams. Bioinformatics. 2021;37(4):580-582doi: 10.1093/bioinformatics/btaa723.
Nagpal, S., Kuntal, B. K., & Mande, S. S. (2021). NetSets.js: a JavaScript framework for compositional assessment and comparison of biological networks through Venn-integrated network diagrams. Bioinformatics (Oxford, England), 37(4), 580-582. https://doi.org/10.1093/bioinformatics/btaa723
Nagpal, Sunil, et al. "NetSets.js: a JavaScript framework for compositional assessment and comparison of biological networks through Venn-integrated network diagrams." Bioinformatics (Oxford, England) vol. 37,4 (2021): 580-582. doi: https://doi.org/10.1093/bioinformatics/btaa723
Nagpal S, Kuntal BK, Mande SS. NetSets.js: a JavaScript framework for compositional assessment and comparison of biological networks through Venn-integrated network diagrams. Bioinformatics. 2021 May 01;37(4):580-582. doi: 10.1093/bioinformatics/btaa723. PMID: 32805035.
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Tools 2021: New methods, new approaches, and a salute to recent developments in protein science.

Protein science : a publication of the Protein Society

Matthews BW.
PMID: 33264460
Protein Sci. 2021 Jan;30(1):5-7. doi: 10.1002/pro.4003. Epub 2020 Dec 02.

No abstract available.

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Matthews BW. Tools 2021: New methods, new approaches, and a salute to recent developments in protein science. Protein Sci. 2020;30(1):5-7doi: 10.1002/pro.4003.
Matthews, B. W. (2021). Tools 2021: New methods, new approaches, and a salute to recent developments in protein science. Protein science : a publication of the Protein Society, 30(1), 5-7. https://doi.org/10.1002/pro.4003
Matthews, Brian W. "Tools 2021: New methods, new approaches, and a salute to recent developments in protein science." Protein science : a publication of the Protein Society vol. 30,1 (2021): 5-7. doi: https://doi.org/10.1002/pro.4003
Matthews BW. Tools 2021: New methods, new approaches, and a salute to recent developments in protein science. Protein Sci. 2021 Jan;30(1):5-7. doi: 10.1002/pro.4003. Epub 2020 Dec 02. PMID: 33264460; PMCID: PMC7737770.
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The impact of compound library size on the performance of scoring functions for structure-based virtual screening.

Briefings in bioinformatics

Fresnais L, Ballester PJ.
PMID: 32568385
Brief Bioinform. 2021 May 20;22(3). doi: 10.1093/bib/bbaa095.

Larger training datasets have been shown to improve the accuracy of machine learning (ML)-based scoring functions (SFs) for structure-based virtual screening (SBVS). In addition, massive test sets for SBVS, known as ultra-large compound libraries, have been demonstrated to enable...

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Fresnais L, Ballester PJ. The impact of compound library size on the performance of scoring functions for structure-based virtual screening. Brief Bioinform. 2021;22(3)doi: 10.1093/bib/bbaa095.
Fresnais, L., & Ballester, P. J. (2021). The impact of compound library size on the performance of scoring functions for structure-based virtual screening. Briefings in bioinformatics, 22(3), . https://doi.org/10.1093/bib/bbaa095
Fresnais, Louison, and Ballester, Pedro J. "The impact of compound library size on the performance of scoring functions for structure-based virtual screening." Briefings in bioinformatics vol. 22,3 (2021). doi: https://doi.org/10.1093/bib/bbaa095
Fresnais L, Ballester PJ. The impact of compound library size on the performance of scoring functions for structure-based virtual screening. Brief Bioinform. 2021 May 20;22(3). doi: 10.1093/bib/bbaa095. PMID: 32568385.
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A method for increasing expressivity of Gene Ontology annotations using a compositional approach.

BMC bioinformatics

Huntley RP, Harris MA, Alam-Faruque Y, Blake JA, Carbon S, Dietze H, Dimmer EC, Foulger RE, Hill DP, Khodiyar VK, Lock A, Lomax J, Lovering RC, Mutowo-Meullenet P, Sawford T, Van Auken K, Wood V, Mungall CJ.
PMID: 24885854
BMC Bioinformatics. 2014 May 21;15:155. doi: 10.1186/1471-2105-15-155.

BACKGROUND: The Gene Ontology project integrates data about the function of gene products across a diverse range of organisms, allowing the transfer of knowledge from model organisms to humans, and enabling computational analyses for interpretation of high-throughput experimental and...

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Huntley RP, Harris MA, Alam-Faruque Y, et al. A method for increasing expressivity of Gene Ontology annotations using a compositional approach. BMC Bioinformatics. 2014;15:155doi: 10.1186/1471-2105-15-155.
Huntley, R. P., Harris, M. A., Alam-Faruque, Y., Blake, J. A., Carbon, S., Dietze, H., Dimmer, E. C., Foulger, R. E., Hill, D. P., Khodiyar, V. K., Lock, A., Lomax, J., Lovering, R. C., Mutowo-Meullenet, P., Sawford, T., Van Auken, K., Wood, V., & Mungall, C. J. (2014). A method for increasing expressivity of Gene Ontology annotations using a compositional approach. BMC bioinformatics, 15155. https://doi.org/10.1186/1471-2105-15-155
Huntley, Rachael P, et al. "A method for increasing expressivity of Gene Ontology annotations using a compositional approach." BMC bioinformatics vol. 15 (2014): 155. doi: https://doi.org/10.1186/1471-2105-15-155
Huntley RP, Harris MA, Alam-Faruque Y, Blake JA, Carbon S, Dietze H, Dimmer EC, Foulger RE, Hill DP, Khodiyar VK, Lock A, Lomax J, Lovering RC, Mutowo-Meullenet P, Sawford T, Van Auken K, Wood V, Mungall CJ. A method for increasing expressivity of Gene Ontology annotations using a compositional approach. BMC Bioinformatics. 2014 May 21;15:155. doi: 10.1186/1471-2105-15-155. PMID: 24885854; PMCID: PMC4039540.
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Showing 1 to 12 of 15 entries