Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Dimitrios Vitsios"'
Autor:
Arwa Raies, Ewa Tulodziecka, James Stainer, Lawrence Middleton, Ryan S. Dhindsa, Pamela Hill, Ola Engkvist, Andrew R. Harper, Slavé Petrovski, Dimitrios Vitsios
Publikováno v:
Communications Biology, Vol 5, Iss 1, Pp 1-16 (2022)
Abstract The druggability of targets is a crucial consideration in drug target selection. Here, we adopt a stochastic semi-supervised ML framework to develop DrugnomeAI, which estimates the druggability likelihood for every protein-coding gene in the
Externí odkaz:
https://doaj.org/article/92d5ddc705404b2bb82579573ccbc7d1
Autor:
Arwa Raies, Ewa Tulodziecka, James Stainer, Lawrence Middleton, Ryan S. Dhindsa, Pamela Hill, Ola Engkvist, Andrew R. Harper, Slavé Petrovski, Dimitrios Vitsios
Publikováno v:
Communications Biology, Vol 6, Iss 1, Pp 1-1 (2023)
Externí odkaz:
https://doaj.org/article/a03931e24d864c288e29026b1ddad7fc
Autor:
Ryan S. Dhindsa, Johan Mattsson, Abhishek Nag, Quanli Wang, Louise V. Wain, Richard Allen, Eleanor M. Wigmore, Kristina Ibanez, Dimitrios Vitsios, Sri V. V. Deevi, Sebastian Wasilewski, Maria Karlsson, Glenda Lassi, Henric Olsson, Daniel Muthas, Susan Monkley, Alex Mackay, Lynne Murray, Simon Young, Carolina Haefliger, FinnGen Consortium, Toby M. Maher, Maria G. Belvisi, Gisli Jenkins, Philip L. Molyneaux, Adam Platt, Slavé Petrovski
Publikováno v:
Communications Biology, Vol 4, Iss 1, Pp 1-8 (2021)
Ryan Dhindsa et al. conducted an exome-wide association study to identify a rare variant in SPDL1 as a risk factor for idiopathic pulmonary fibrosis (IPF). Their findings implicate mitotic checkpoint signalling as a new mechanism underlying IPF.
Externí odkaz:
https://doaj.org/article/5ca8ca31c47044f2a6b834855f2cbf1a
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-14 (2021)
Intolerance to variation is a strong indicator of disease relevance for coding regions of the human genome. Here, the authors present JARVIS, a deep learning method integrating intolerance to variation in non-coding regions and sequence-specific anno
Externí odkaz:
https://doaj.org/article/4a6d20095a0b4f49bb6cbd6b031c99c8
Autor:
Abhishek Nag, Ryan S. Dhindsa, Lawrence Middleton, Xiao Jiang, Dimitrios Vitsios, Eleanor Wigmore, Erik L. Allman, Anna Reznichenko, Keren Carss, Katherine R. Smith, Quanli Wang, Benjamin Challis, Dirk S. Paul, Andrew R. Harper, Slavé Petrovski
Publikováno v:
The American Journal of Human Genetics. 110:487-498
Autor:
Lawrence Middleton, Andrew R Harper, Abhishek Nag, Quanli Wang, Anna Reznichenko, Dimitrios Vitsios, Slavé Petrovski
Publikováno v:
Nucleic Acids Research. 50:4289-4301
Large-scale phenome-wide association studies performed using densely-phenotyped cohorts such as the UK Biobank (UKB), reveal many statistically robust gene-phenotype relationships for both clinical and continuous traits. Here, we present Gene-SCOUT,
Autor:
Abhishek Nag, Ryan S. Dhindsa, Jonathan Mitchell, Chirag Vasavda, Andrew R. Harper, Dimitrios Vitsios, Andrea Ahnmark, Bilada Bilican, Katja Madeyski-Bengtson, Bader Zarrouki, Anthony W. Zoghbi, Quanli Wang, Katherine R. Smith, Jesus Alegre-Díaz, Pablo Kuri-Morales, Jaime Berumen, Roberto Tapia-Conyer, Jonathan Emberson, Jason M. Torres, Rory Collins, David M. Smith, Benjamin Challis, Dirk S. Paul, Mohammad Bohlooly-Y, Mike Snowden, David Baker, Regina Fritsche-Danielson, Menelas N. Pangalos, Slavé Petrovski
We performed collapsing analyses on 454,796 UK Biobank (UKB) exomes to detect gene-level associations with diabetes. Recessive carriers of nonsynonymous variants in MAP3K15 were 30% less likely to develop diabetes ( P = 5.7 × 10 −10 ) and had lowe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3a682c76a1eca49d8219fc25c810730
https://doi.org/10.1126/sciadv.add5430
https://doi.org/10.1126/sciadv.add5430
Autor:
Ryan S. Dhindsa, Blake Weido, Justin S. Dhindsa, Arya J. Shetty, Chloe Sands, Slavé Petrovski, Dimitrios Vitsios, Anthony W. Zoghbi
Despite great progress in the identification of neurodevelopmental disorder (NDD) risk genes, there are thousands that remain to be discovered. Computational tools that provide accurate gene-level predictions of NDD risk can significantly reduce the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b598b09a50696375e27f7f0c446290d0
https://doi.org/10.1101/2022.11.21.517436
https://doi.org/10.1101/2022.11.21.517436
Autor:
Abhishek, Nag, Ryan S, Dhindsa, Jonathan, Mitchell, Chirag, Vasavda, Andrew R, Harper, Dimitrios, Vitsios, Andrea, Ahnmark, Bilada, Bilican, Katja, Madeyski-Bengtson, Bader, Zarrouki, Anthony W, Zoghbi, Quanli, Wang, Katherine R, Smith, Jesus, Alegre-Díaz, Pablo, Kuri-Morales, Jaime, Berumen, Roberto, Tapia-Conyer, Jonathan, Emberson, Jason M, Torres, Rory, Collins, David M, Smith, Benjamin, Challis, Dirk S, Paul, Mohammad, Bohlooly-Y, Mike, Snowden, David, Baker, Regina, Fritsche-Danielson, Menelas N, Pangalos, Slavé, Petrovski
Publikováno v:
Science advances. 8(46)
We performed collapsing analyses on 454,796 UK Biobank (UKB) exomes to detect gene-level associations with diabetes. Recessive carriers of nonsynonymous variants in
Autor:
Ryan S. Dhindsa, Quanli Wang, Dimitrios Vitsios, Oliver S. Burren, Fengyuan Hu, James E. DiCarlo, Leonid Kruglyak, Daniel G. MacArthur, Matthew E. Hurles, Slavé Petrovski
Publikováno v:
Am J Hum Genet
SummarySynonymous mutations change the DNA sequence of a gene without affecting the amino acid sequence of the encoded protein. Although emerging evidence suggests that synonymous mutations can impact RNA splicing, translational efficiency, and mRNA
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::866ec13855c8cacd54b3922e55dbbc8c
https://doi.org/10.1101/2022.07.13.499964
https://doi.org/10.1101/2022.07.13.499964