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- Research data . 2020EnglishAuthors:Choudhary, Neha; Jaraquemada-Peláez, Marı́a de Guadalupe; Zarschler, Kristof; Wang, Xiaozhu; Radchenko, Valery; Kubeil, Manja; Stephan, Holger; Orvig, Chris;Choudhary, Neha; Jaraquemada-Peláez, Marı́a de Guadalupe; Zarschler, Kristof; Wang, Xiaozhu; Radchenko, Valery; Kubeil, Manja; Stephan, Holger; Orvig, Chris;Publisher: Cambridge Crystallographic Data CentreProject: NSERC , CIHR
Related Article: Neha Choudhary, Marı́a de Guadalupe Jaraquemada-Peláez, Kristof Zarschler, Xiaozhu Wang, Valery Radchenko, Manja Kubeil, Holger Stephan, Chris Orvig|2020|Inorg.Chem.|59|5728|doi:10.1021/acs.inorgchem.0c00509
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . Image . 2015Open AccessAuthors:Sukjae Kang; Chuljung Kwak; Jaehyun Lee; Su-Eon Sim; Jaehoon Shim; Taehyuk Choi; Collingridge, Graham; Zhuo, Min; Bong-Kiun Kaang;Sukjae Kang; Chuljung Kwak; Jaehyun Lee; Su-Eon Sim; Jaehoon Shim; Taehyuk Choi; Collingridge, Graham; Zhuo, Min; Bong-Kiun Kaang;Publisher: FigshareProject: NSERC , CIHR
Control data of optogenetic activation of ACC PV-positive interneurons. A, Result of the PV-ChR2 saline group. There was no light effect either before (off: 5.09 ± 0.22 g, on: 4.84 ± 0.09 g; n = 6) or after saline injection (off: 5.18 ± 0.18 g, on: 4.79 ± 0.23 g; n = 6). B, Result of the WT-ChR2 CFA group. There was no light effect before (off: 5.18 ± 0.13 g, on: 5.12 ± 0.12 g; n = 8) or after CFA (off: 3.33 ± 0.12 g, on: 3.58 ± 0.19 g; n = 8). There was only statistically significant effect of CFA treatment per se (p
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2021Open AccessAuthors:Novakovsky, Gherman; Saraswat, Manu; Fornes, Oriol; Mostafavi, Sara; Wasserman, Wyeth W.;Novakovsky, Gherman; Saraswat, Manu; Fornes, Oriol; Mostafavi, Sara; Wasserman, Wyeth W.;Publisher: figshareProject: NSERC , CIHR
Additional file 12: Table S1. Total number of ones, zeros and nulls in the sparse matrix for the 163 TFs used in this study.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . Bioentity . 2018Project: NSERC , CIHR
- Research data . 2017Open AccessAuthors:Gagarinova, Alla; Phanse, Sadhna; Miroslaw Cygler; Babu, Mohan;Gagarinova, Alla; Phanse, Sadhna; Miroslaw Cygler; Babu, Mohan;Publisher: Taylor & FrancisProject: NSERC , CIHR
Introduction: The threat bacterial pathogens pose to human health is increasing with the number and distribution of antibiotic-resistant bacteria, while the rate of discovery of new antimicrobials dwindles. Proteomics is playing key roles in understanding the molecular mechanisms of bacterial pathogenesis, and in identifying disease outcome determinants. The physical associations identified by proteomics can provide the means to develop pathogen-specific treatment methods that reduce the spread of antibiotic resistance and alleviate the negative effects of broad-spectrum antibiotics on beneficial bacteria. Areas covered: This review discusses recent trends in proteomics and introduces new and developing approaches that can be applied to the study of protein-protein interactions (PPIs) underlying bacterial pathogenesis. The approaches examined encompass options for mapping proteomes as well as stable and transient interactions in vivo and in vitro. We also explored the coverage of bacterial and human-bacterial PPIs, knowledge gaps in this area, and how they can be filled. Expert commentary: Identifying potential antimicrobial candidates is confounded by the complex molecular biology of bacterial pathogenesis and the lack of knowledge about PPIs underlying this process. Proteomics approaches can offer new perspectives for mechanistic insights and identify essential targets for guiding the discovery of next generation antimicrobials.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . Bioentity . 2017Project: NSERC , NIH | The Catalytic Mechanism o... (5R01GM088656-03), CIHR
- Research data . 2018Open AccessAuthors:Yifeng Li; Wenqiang Shi; Wyeth Wasserman;Yifeng Li; Wenqiang Shi; Wyeth Wasserman;Publisher: figshareProject: NSERC , NIH | Computational Resources f... (1R01GM084875-01A2), CIHR
Genome-wide predictions of cis-regulatory regions for all six cell types. (ZIP 20400 kb)
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.
1,434 Research products, page 1 of 144
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- Research data . 2020EnglishAuthors:Choudhary, Neha; Jaraquemada-Peláez, Marı́a de Guadalupe; Zarschler, Kristof; Wang, Xiaozhu; Radchenko, Valery; Kubeil, Manja; Stephan, Holger; Orvig, Chris;Choudhary, Neha; Jaraquemada-Peláez, Marı́a de Guadalupe; Zarschler, Kristof; Wang, Xiaozhu; Radchenko, Valery; Kubeil, Manja; Stephan, Holger; Orvig, Chris;Publisher: Cambridge Crystallographic Data CentreProject: NSERC , CIHR
Related Article: Neha Choudhary, Marı́a de Guadalupe Jaraquemada-Peláez, Kristof Zarschler, Xiaozhu Wang, Valery Radchenko, Manja Kubeil, Holger Stephan, Chris Orvig|2020|Inorg.Chem.|59|5728|doi:10.1021/acs.inorgchem.0c00509
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . Image . 2015Open AccessAuthors:Sukjae Kang; Chuljung Kwak; Jaehyun Lee; Su-Eon Sim; Jaehoon Shim; Taehyuk Choi; Collingridge, Graham; Zhuo, Min; Bong-Kiun Kaang;Sukjae Kang; Chuljung Kwak; Jaehyun Lee; Su-Eon Sim; Jaehoon Shim; Taehyuk Choi; Collingridge, Graham; Zhuo, Min; Bong-Kiun Kaang;Publisher: FigshareProject: NSERC , CIHR
Control data of optogenetic activation of ACC PV-positive interneurons. A, Result of the PV-ChR2 saline group. There was no light effect either before (off: 5.09 ± 0.22 g, on: 4.84 ± 0.09 g; n = 6) or after saline injection (off: 5.18 ± 0.18 g, on: 4.79 ± 0.23 g; n = 6). B, Result of the WT-ChR2 CFA group. There was no light effect before (off: 5.18 ± 0.13 g, on: 5.12 ± 0.12 g; n = 8) or after CFA (off: 3.33 ± 0.12 g, on: 3.58 ± 0.19 g; n = 8). There was only statistically significant effect of CFA treatment per se (p
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2021Open AccessAuthors:Novakovsky, Gherman; Saraswat, Manu; Fornes, Oriol; Mostafavi, Sara; Wasserman, Wyeth W.;Novakovsky, Gherman; Saraswat, Manu; Fornes, Oriol; Mostafavi, Sara; Wasserman, Wyeth W.;Publisher: figshareProject: NSERC , CIHR
Additional file 12: Table S1. Total number of ones, zeros and nulls in the sparse matrix for the 163 TFs used in this study.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . Bioentity . 2018Project: NSERC , CIHR
- Research data . 2017Open AccessAuthors:Gagarinova, Alla; Phanse, Sadhna; Miroslaw Cygler; Babu, Mohan;Gagarinova, Alla; Phanse, Sadhna; Miroslaw Cygler; Babu, Mohan;Publisher: Taylor & FrancisProject: NSERC , CIHR
Introduction: The threat bacterial pathogens pose to human health is increasing with the number and distribution of antibiotic-resistant bacteria, while the rate of discovery of new antimicrobials dwindles. Proteomics is playing key roles in understanding the molecular mechanisms of bacterial pathogenesis, and in identifying disease outcome determinants. The physical associations identified by proteomics can provide the means to develop pathogen-specific treatment methods that reduce the spread of antibiotic resistance and alleviate the negative effects of broad-spectrum antibiotics on beneficial bacteria. Areas covered: This review discusses recent trends in proteomics and introduces new and developing approaches that can be applied to the study of protein-protein interactions (PPIs) underlying bacterial pathogenesis. The approaches examined encompass options for mapping proteomes as well as stable and transient interactions in vivo and in vitro. We also explored the coverage of bacterial and human-bacterial PPIs, knowledge gaps in this area, and how they can be filled. Expert commentary: Identifying potential antimicrobial candidates is confounded by the complex molecular biology of bacterial pathogenesis and the lack of knowledge about PPIs underlying this process. Proteomics approaches can offer new perspectives for mechanistic insights and identify essential targets for guiding the discovery of next generation antimicrobials.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . Bioentity . 2017Project: NSERC , NIH | The Catalytic Mechanism o... (5R01GM088656-03), CIHR
- Research data . 2018Open AccessAuthors:Yifeng Li; Wenqiang Shi; Wyeth Wasserman;Yifeng Li; Wenqiang Shi; Wyeth Wasserman;Publisher: figshareProject: NSERC , NIH | Computational Resources f... (1R01GM084875-01A2), CIHR
Genome-wide predictions of cis-regulatory regions for all six cell types. (ZIP 20400 kb)
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.