Development of Bioinformatics Infrastructure for Genomics Research:
- Mulder, Nicola J, Adebiyi, Ezekiel, Adebiyi, Marion, Adeyemi, Seun, Ahmed, Azza, Ahmed, Rehab, Akanle, Bola, Alibi, Mohamed, Armstrong, Don L, Aron, Shaun, Ashano, Efejiro, Baichoo, Shakuntala, Benkahla, Alia, Brown, David K, Chimusa, Emile Rugamika, Fadlelmola, Faisal M, Falola, Dare, Fatumo, Segun, Ghedira, Kais, Ghouila, Amel, Hazelhurst, Scott, Itunuoluwa Isewon, Segun Jung, Kassim, Samar Kamal, Kayondo, Jonathan K, Mbiyavanga, Mamana, Meintjes, Ayton, Mohammed, Somia, Mosaku, Abayomi, Moussa, Ahmed, Muhammd, Mustafa, Mungloo-Dilmohamud, Zahra, Nashiru, Oyekanmi, Odia, Trust, Okafor, Adaobi, Oladipo, Olaleye, Osamor, Victor, Oyelade, Jellili, Sadki, Khalid, Salifu, Samson Pandam, Soyemi, Jumoke, Panji, Sumir, Radouani, Fouzia, Souiai, Oussama, Tastan Bishop, Özlem
- Authors: Mulder, Nicola J , Adebiyi, Ezekiel , Adebiyi, Marion , Adeyemi, Seun , Ahmed, Azza , Ahmed, Rehab , Akanle, Bola , Alibi, Mohamed , Armstrong, Don L , Aron, Shaun , Ashano, Efejiro , Baichoo, Shakuntala , Benkahla, Alia , Brown, David K , Chimusa, Emile Rugamika , Fadlelmola, Faisal M , Falola, Dare , Fatumo, Segun , Ghedira, Kais , Ghouila, Amel , Hazelhurst, Scott , Itunuoluwa Isewon , Segun Jung , Kassim, Samar Kamal , Kayondo, Jonathan K , Mbiyavanga, Mamana , Meintjes, Ayton , Mohammed, Somia , Mosaku, Abayomi , Moussa, Ahmed , Muhammd, Mustafa , Mungloo-Dilmohamud, Zahra , Nashiru, Oyekanmi , Odia, Trust , Okafor, Adaobi , Oladipo, Olaleye , Osamor, Victor , Oyelade, Jellili , Sadki, Khalid , Salifu, Samson Pandam , Soyemi, Jumoke , Panji, Sumir , Radouani, Fouzia , Souiai, Oussama , Tastan Bishop, Özlem
- Date: 2017
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/148239 , vital:38722 , DOI: 10.1016/j.gheart.2017.01.005
- Description: Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet's role has evolved in response to changing needs from the consortium and the African bioinformatics community.
- Full Text:
- Date Issued: 2017
- Authors: Mulder, Nicola J , Adebiyi, Ezekiel , Adebiyi, Marion , Adeyemi, Seun , Ahmed, Azza , Ahmed, Rehab , Akanle, Bola , Alibi, Mohamed , Armstrong, Don L , Aron, Shaun , Ashano, Efejiro , Baichoo, Shakuntala , Benkahla, Alia , Brown, David K , Chimusa, Emile Rugamika , Fadlelmola, Faisal M , Falola, Dare , Fatumo, Segun , Ghedira, Kais , Ghouila, Amel , Hazelhurst, Scott , Itunuoluwa Isewon , Segun Jung , Kassim, Samar Kamal , Kayondo, Jonathan K , Mbiyavanga, Mamana , Meintjes, Ayton , Mohammed, Somia , Mosaku, Abayomi , Moussa, Ahmed , Muhammd, Mustafa , Mungloo-Dilmohamud, Zahra , Nashiru, Oyekanmi , Odia, Trust , Okafor, Adaobi , Oladipo, Olaleye , Osamor, Victor , Oyelade, Jellili , Sadki, Khalid , Salifu, Samson Pandam , Soyemi, Jumoke , Panji, Sumir , Radouani, Fouzia , Souiai, Oussama , Tastan Bishop, Özlem
- Date: 2017
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/148239 , vital:38722 , DOI: 10.1016/j.gheart.2017.01.005
- Description: Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet's role has evolved in response to changing needs from the consortium and the African bioinformatics community.
- Full Text:
- Date Issued: 2017
Structure-based analysis of single nucleotide variants in the renin-angiotensinogen complex:
- Brown, David K, Olivier, Sheik Amamuddy, Tastan Bishop, Özlem
- Authors: Brown, David K , Olivier, Sheik Amamuddy , Tastan Bishop, Özlem
- Date: 2017
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/147994 , vital:38700 , https://doi.org/10.1016/j.gheart.2017.01.006
- Description: The renin-angiotensin system (RAS) plays an important role in regulating blood pressure and controlling sodium levels in the blood. Hyperactivity of this system has been linked to numerous conditions including hypertension, kidney disease, and congestive heart failure. Three classes of drugs have been developed to inhibit RAS. In this study, we provide a structure-based analysis of the effect of single nucleotide variants (SNVs) on the interaction between renin and angiotensinogen with the aim of revealing important residues and potentially damaging variants for further inhibitor design purposes.
- Full Text:
- Date Issued: 2017
- Authors: Brown, David K , Olivier, Sheik Amamuddy , Tastan Bishop, Özlem
- Date: 2017
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/147994 , vital:38700 , https://doi.org/10.1016/j.gheart.2017.01.006
- Description: The renin-angiotensin system (RAS) plays an important role in regulating blood pressure and controlling sodium levels in the blood. Hyperactivity of this system has been linked to numerous conditions including hypertension, kidney disease, and congestive heart failure. Three classes of drugs have been developed to inhibit RAS. In this study, we provide a structure-based analysis of the effect of single nucleotide variants (SNVs) on the interaction between renin and angiotensinogen with the aim of revealing important residues and potentially damaging variants for further inhibitor design purposes.
- Full Text:
- Date Issued: 2017
The role of structural bioinformatics in drug discovery via computational SNP analysis–a proposed protocol for analyzing variation at the protein level:
- Brown, David K, Tastan Bishop, Özlem
- Authors: Brown, David K , Tastan Bishop, Özlem
- Date: 2017
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/162914 , vital:40996 , doi: 10.1016/j.gheart.2017.01.009
- Description: With the completion of the human genome project at the beginning of the 21st century, the biological sciences entered an unprecedented age of data generation, and made its first steps towards an era of personalized medicine. This abundance of sequence data has led to the proliferation of numerous sequence-based techniques for associating variation with disease, such as Genome-Wide Association Studies (GWAS) and Candidate Gene Association Studies (CGAS). However, these statistical methods do not provide an understanding of the functional effects of variation. Structure-based drug discovery and design is increasingly incorporating structural bioinformatics techniques to model and analyze protein targets, perform large scale virtual screening to identify hit to lead compounds, and simulate molecular interactions. These techniques are fast, cost-effective, and complement existing experimental techniques such as High Throughput Sequencing (HTS).
- Full Text:
- Date Issued: 2017
- Authors: Brown, David K , Tastan Bishop, Özlem
- Date: 2017
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/162914 , vital:40996 , doi: 10.1016/j.gheart.2017.01.009
- Description: With the completion of the human genome project at the beginning of the 21st century, the biological sciences entered an unprecedented age of data generation, and made its first steps towards an era of personalized medicine. This abundance of sequence data has led to the proliferation of numerous sequence-based techniques for associating variation with disease, such as Genome-Wide Association Studies (GWAS) and Candidate Gene Association Studies (CGAS). However, these statistical methods do not provide an understanding of the functional effects of variation. Structure-based drug discovery and design is increasingly incorporating structural bioinformatics techniques to model and analyze protein targets, perform large scale virtual screening to identify hit to lead compounds, and simulate molecular interactions. These techniques are fast, cost-effective, and complement existing experimental techniques such as High Throughput Sequencing (HTS).
- Full Text:
- Date Issued: 2017
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