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Ali Torkamani
Scripps Research Institute
107Publications
38H-index
5,012Citations
Publications 109
Newest
#1Seok Kyu Kang (NU: Northwestern University)H-Index: 1
#2Carlos G. Vanoye (NU: Northwestern University)H-Index: 29
Last.Jennifer A. Kearney (NU: Northwestern University)H-Index: 26
view all 32 authors...
2 CitationsSource
A gene is considered essential if loss of function results in loss of viability, fitness or in disease. This concept is well established for coding genes; however, non-coding regions are thought less likely to be determinants of critical functions. Here we train a machine learning model using functional, mutational and structural features, including new genome essentiality metrics, 3D genome organization and enhancer reporter data to identify deleterious variants in non-coding regions. We assess...
2 CitationsSource
Artificial intelligence (AI) is the development of computer systems that are able to perform tasks that normally require human intelligence. Advances in AI software and hardware, especially deep learning algorithms and the graphics processing units (GPUs) that power their training, have led to a recent and rapidly increasing interest in medical AI applications. In clinical diagnostics, AI-based computer vision approaches are poised to revolutionize image-based diagnostics, while other AI subtype...
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Whole-exome sequencing (WES) has become an efficient diagnostic test for patients with likely monogenic conditions such as rare idiopathic diseases or sudden unexplained death. Yet, many cases remain undiagnosed. Here, we report the added diagnostic yield achieved for 101 WES cases re-analyzed 1 to 7 years after initial analysis. Of the 101 WES cases, 51 were rare idiopathic disease cases and 50 were postmortem “molecular autopsy” cases of early sudden unexplained death. Variants considered for ...
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#1Anita Chandrasekaran (Scripps Health)H-Index: 1
#2Bhuvan Molparia (Scripps Research Institute)H-Index: 7
Last.Gauree G. Konijeti (Scripps Health)H-Index: 5
view all 9 authors...
Source
#1Seok Kyu Kang (NU: Northwestern University)H-Index: 1
#2Carlos G. Vanoye (NU: Northwestern University)H-Index: 29
Last.Jennifer A. Kearney (NU: Northwestern University)H-Index: 26
view all 32 authors...
Pathogenic variants in KCNB1 , encoding the voltage-gated potassium channel K V 2.1, are associated with developmental and epileptic encephalopathies (DEE). Previous functional studies on a limited number of KCNB1 variants indicated a range of molecular mechanisms by which variants affect channel function, including loss of voltage sensitivity, loss of ion selectivity, and reduced cell-surface expression. We evaluated a series of 17 KCNB1 variants associated with DEE or neurodevelopmental disord...
1 CitationsSource
#1Ali Torkamani (Scripps Health)H-Index: 38
#2Eric J. Topol (Scripps Health)H-Index: 178
Obesity is one of the most serious health challenges of our time. In this issue of Cell, Khera and co-authors demonstrate the striking ability of genetics, in the form of a polygenic risk score, to identify those individuals at high risk for obesity. This genetic risk expresses itself early as childhood obesity, reinforcing the notion that early prevention is essential to combatting the obesity epidemic.
1 CitationsSource
#1Aditya Kumar (UCSD: University of California, San Diego)H-Index: 5
#2Stephanie Thomas (UCSD: University of California, San Diego)H-Index: 1
Last.Adam J. Engler (UCSD: University of California, San Diego)H-Index: 41
view all 13 authors...
How common polymorphisms in noncoding genome regions can regulate cellular function remains largely unknown. Here we show that cardiac fibrosis, mimicked using a hydrogel with controllable stiffness, affects the regulation of the phenotypes of human cardiomyocytes by a portion of the long noncoding RNA ANRIL, the gene of which is located in the disease-associated 9p21 locus. In a physiological environment, cultured cardiomyocytes derived from induced pluripotent stem cells obtained from patients...
2 CitationsSource
#2Cynthia CheungH-Index: 3
Last.Cinnamon S. BlossH-Index: 37
view all 4 authors...
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#1J C Zou (Stanford University)H-Index: 32
#2Mikael Huss (KI: Karolinska Institutet)H-Index: 23
Last.Amalio Telenti (Scripps Research Institute)H-Index: 81
view all 6 authors...
Deep learning methods are a class of machine learning techniques capable of identifying highly complex patterns in large datasets. Here, we provide a perspective and primer on deep learning applications for genome analysis. We discuss successful applications in the fields of regulatory genomics, variant calling and pathogenicity scores. We include general guidance for how to effectively use deep learning methods as well as a practical guide to tools and resources. This primer is accompanied by a...
39 CitationsSource
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