A
Adam P. Arkin
Researcher at Lawrence Berkeley National Laboratory
Publications - 483
Citations - 65570
Adam P. Arkin is an academic researcher from Lawrence Berkeley National Laboratory. The author has contributed to research in topics: Gene & Genome. The author has an hindex of 96, co-authored 447 publications receiving 56301 citations. Previous affiliations of Adam P. Arkin include University of Missouri & California Institute for Quantitative Biosciences.
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Journal ArticleDOI
FastTree 2--approximately maximum-likelihood trees for large alignments.
TL;DR: Improvements to FastTree are described that improve its accuracy without sacrificing scalability, and FastTree 2 allows the inference of maximum-likelihood phylogenies for huge alignments.
Journal ArticleDOI
Functional profiling of the Saccharomyces cerevisiae genome.
Guri Giaever,Angela M. Chu,Li Ni,Carla Connelly,Linda Riles,Steeve Veronneau,Sally Dow,Ankuta Lucau-Danila,Keith Anderson,Bruno André,Adam P. Arkin,Anna Astromoff,Mohamed El Bakkoury,Rhonda Bangham,Rocío Benito,Sophie Brachat,Stefano Campanaro,Matt Curtiss,Karen Davis,Adam M. Deutschbauer,K. D. Entian,Patrick Flaherty,Françoise Foury,David J. Garfinkel,Mark Gerstein,Deanna Gotte,Ulrich Güldener,Johannes H. Hegemann,Svenja Hempel,Zelek S. Herman,Daniel F. Jaramillo,Diane E. Kelly,Steven L. Kelly,Peter Kötter,Darlene LaBonte,David C. Lamb,Ning Lan,Hong Liang,Hong Liao,Lucy Y. Liu,Chuanyun Luo,Marc Lussier,Rong Mao,Patrice Menard,Siew Loon Ooi,José L. Revuelta,Christopher J. Roberts,Matthias Rose,Petra Ross-Macdonald,Bart Scherens,Greg Schimmack,Brenda Shafer,Daniel D. Shoemaker,Sharon Sookhai-Mahadeo,Reginald Storms,Jeffrey N. Strathern,Giorgio Valle,Marleen Voet,Guido Volckaert,Ching Yun Wang,Teresa R. Ward,Julie Wilhelmy,Elizabeth A. Winzeler,Yonghong Yang,Grace Yen,Elaine M. Youngman,Kexin Yu,Howard Bussey,Jef D. Boeke,Michael Snyder,Peter Philippsen,Ronald W. Davis,Mark Johnston +72 more
TL;DR: It is shown that previously known and new genes are necessary for optimal growth under six well-studied conditions: high salt, sorbitol, galactose, pH 8, minimal medium and nystatin treatment, and less than 7% of genes that exhibit a significant increase in messenger RNA expression are also required for optimal Growth in four of the tested conditions.
Journal ArticleDOI
Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression.
Lei S. Qi,Matthew H. Larson,Luke A. Gilbert,Jennifer A. Doudna,Jonathan S. Weissman,Adam P. Arkin,Adam P. Arkin,Wendell A. Lim +7 more
TL;DR: This RNA-guided DNA recognition platform provides a simple approach for selectively perturbing gene expression on a genome-wide scale and can efficiently repress expression of targeted genes in Escherichia coli, with no detectable off-target effects.
Journal ArticleDOI
FastTree: Computing Large Minimum Evolution Trees with Profiles instead of a Distance Matrix
TL;DR: FastTree is a method for constructing large phylogenies and for estimating their reliability, instead of storing a distance matrix, that uses sequence profiles of internal nodes in the tree to implement Neighbor-Joining and uses heuristics to quickly identify candidate joins.
Journal ArticleDOI
The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models.
Michael Hucka,Andrew Finney,Herbert M. Sauro,Hamid Bolouri,Hamid Bolouri,John Doyle,Hiroaki Kitano,Adam P. Arkin,Benjamin Bornstein,Dennis Bray,Athel Cornish-Bowden,Autumn A. Cuellar,S. Dronov,E. D. Gilles,Martin Ginkel,V. Gor,Igor Goryanin,W. J. Hedley,T. C. Hodgman,J.-H.S. Hofmeyr,Peter Hunter,Nick Juty,J. L. Kasberger,Andreas Kremling,Ursula Kummer,N Le Novère,Leslie M. Loew,D. Lucio,Pedro Mendes,E. Minch,Eric Mjolsness,Yoichi Nakayama,Melanie R. Nelson,Poul M. F. Nielsen,T. Sakurada,James C. Schaff,Bruce E. Shapiro,Thomas S. Shimizu,H. D. Spence,Jörg Stelling,Koichi Takahashi,Masaru Tomita,John Wagner,J. Wang +43 more
TL;DR: This work summarizes the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks, a software-independent language for describing models common to research in many areas of computational biology.