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Maxwell Sanderford

Researcher at Temple University

Publications -  22
Citations -  485

Maxwell Sanderford is an academic researcher from Temple University. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 9, co-authored 17 publications receiving 236 citations. Previous affiliations of Maxwell Sanderford include Arizona State University & King Abdulaziz University.

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TimeTree 5: An Expanded Resource for Species Divergence Times

TL;DR: The fifth edition of the TimeTree of Life resource (TToL5), a product of the timetree of life project that aims to synthesize published molecular timetrees and make evolutionary knowledge easily accessible to all, is presented.
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Evolutionary diagnosis method for variants in personal exomes

TL;DR: The lack of a common file format has been a significant barrier to the effective sharing of software tools and analysis techniques, and CXIDB is standardized on CXI files, which are based on the HDF5 format.
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Biological relevance of computationally predicted pathogenicity of noncoding variants.

TL;DR: A significant disconnect is found to exist between the statistical modelling and biological performance of predictive approaches and the fundamental reasons underlying these deficiencies are discussed and it is suggested that future improvements of computational predictions need to address confounding of allelic, positional and regional effects.
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An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic.

TL;DR: The most recent common ancestor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was reconstructed through a novel application and advancement of computational methods initially developed to infer the mutational history of tumor cells in a patient as discussed by the authors.
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MEGA-MD: molecular evolutionary genetics analysis software with mutational diagnosis of amino acid variation

TL;DR: The Molecular Evolutionary Genetics Analysis software with mutational diagnosis (MEGA-MD) is a suite of tools developed to forecast the deleteriousness of ns SNVs using multiple methods and to explore nsSNVs in the context of the variability permitted in the long-term evolution of the affected position.