F
Fernando Izquierdo-Carrasco
Researcher at Heidelberg Institute for Theoretical Studies
Publications - 17
Citations - 2862
Fernando Izquierdo-Carrasco is an academic researcher from Heidelberg Institute for Theoretical Studies. The author has contributed to research in topics: Phylogenomics & Likelihood function. The author has an hindex of 9, co-authored 17 publications receiving 2401 citations. Previous affiliations of Fernando Izquierdo-Carrasco include Exelixis.
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Journal ArticleDOI
Phylogenomics resolves the timing and pattern of insect evolution
Bernhard Misof,Shanlin Liu,Karen Meusemann,Ralph S. Peters,Alexander Donath,Christoph Mayer,Paul B. Frandsen,Jessica L. Ware,Tomas Flouri,Rolf G. Beutel,Oliver Niehuis,Malte Petersen,Fernando Izquierdo-Carrasco,Torsten Wappler,Jes Rust,Andre J. Aberer,Ulrike Aspöck,Ulrike Aspöck,Horst Aspöck,Daniela Bartel,Alexander Blanke,Simon Berger,Alexander Böhm,Thomas R. Buckley,Brett Calcott,Junqing Chen,Frank Friedrich,Makiko Fukui,Mari Fujita,Carola Greve,Peter Grobe,Shengchang Gu,Ying Huang,Lars S. Jermiin,Akito Y. Kawahara,Lars Krogmann,Martin Kubiak,Robert Lanfear,Robert Lanfear,Robert Lanfear,Harald Letsch,Yiyuan Li,Zhenyu Li,Jiguang Li,Haorong Lu,Ryuichiro Machida,Yuta Mashimo,Pashalia Kapli,Pashalia Kapli,Duane D. McKenna,Guanliang Meng,Yasutaka Nakagaki,José Luis Navarrete-Heredia,Michael Ott,Yanxiang Ou,Günther Pass,Lars Podsiadlowski,Hans Pohl,Björn M. von Reumont,Kai Schütte,Kaoru Sekiya,Shota Shimizu,Adam Slipinski,Alexandros Stamatakis,Alexandros Stamatakis,Wenhui Song,Xu Su,Nikolaus U. Szucsich,Meihua Tan,Xuemei Tan,Min Tang,Jingbo Tang,Gerald Timelthaler,Shigekazu Tomizuka,Michelle D. Trautwein,Xiaoli Tong,Toshiki Uchifune,Manfred Walzl,Brian M. Wiegmann,Jeanne Wilbrandt,Benjamin Wipfler,Thomas K. F. Wong,Qiong Wu,Gengxiong Wu,Yinlong Xie,Shenzhou Yang,Qing Yang,David K. Yeates,Kazunori Yoshizawa,Qing Zhang,Rui Zhang,Wenwei Zhang,Yunhui Zhang,Jing Zhao,Chengran Zhou,Lili Zhou,Tanja Ziesmann,Shijie Zou,Yingrui Li,Xun Xu,Yong Zhang,Huanming Yang,Jian Wang,Jun Wang,Karl M. Kjer,Xin Zhou +105 more
TL;DR: The phylogeny of all major insect lineages reveals how and when insects diversified and provides a comprehensive reliable scaffold for future comparative analyses of evolutionary innovations among insects.
Journal ArticleDOI
Metagenomic species profiling using universal phylogenetic marker genes
Shinichi Sunagawa,Daniel R. Mende,Georg Zeller,Fernando Izquierdo-Carrasco,Simon Berger,Jens Roat Kultima,Luis Pedro Coelho,Manimozhiyan Arumugam,Julien Tap,Henrik Nielsen,Simon Rasmussen,Søren Brunak,Oluf Pedersen,Francisco Guarner,Willem M. de Vos,Jun Wang,Junhua Li,Joël Doré,S. Dusko Ehrlich,Alexandros Stamatakis,Peer Bork +20 more
TL;DR: To quantify known and unknown microorganisms at species-level resolution using shotgun sequencing data, a method that establishes metagenomic operational taxonomic units (mOTUs) based on single-copy phylogenetic marker genes is developed.
Journal ArticleDOI
RAxML-Light
Alexandros Stamatakis,Andre J. Aberer,C. Goll,Stephen A. Smith,S.A. Berger,Fernando Izquierdo-Carrasco +5 more
TL;DR: RAxML-Light is described, a tool for large-scale phylogenetic inference on supercomputers under maximum likelihood that implements a light-weight checkpointing mechanism, deploys 128-bit and 256-bit vector intrinsics, offers two orthogonal memory saving techniques and provides a fine-grain production-level message passing interface parallelization of the likelihood function.
Journal ArticleDOI
The phylogenetic likelihood library.
Tomas Flouri,Fernando Izquierdo-Carrasco,Diego Darriba,Andre J. Aberer,Lam Tung Nguyen,Bui Quang Minh,A. Von Haeseler,Alexandros Stamatakis +7 more
TL;DR: The Phylogenetic Likelihood Library is introduced, a highly optimized application programming interface for developing likelihood-based phylogenetic inference and postanalysis software that improves the sequential performance of current software by a factor of 2–10 while requiring only 1 month of programming time for integration.
Journal ArticleDOI
Algorithms, data structures, and numerics for likelihood-based phylogenetic inference of huge trees
TL;DR: A new search strategy is developed that can reduce the time required for tree inferences by more than 50% while yielding equally good trees for well-chosen starting trees and issues pertaining to the numerical stability of the Γ model of rate heterogeneity on very large trees are addressed.