F
Francisco J. Planes
Researcher at University of Navarra
Publications - 54
Citations - 1953
Francisco J. Planes is an academic researcher from University of Navarra. The author has contributed to research in topics: Metabolic network & Context (language use). The author has an hindex of 17, co-authored 47 publications receiving 1491 citations. Previous affiliations of Francisco J. Planes include University of Jena & Brunel University London.
Papers
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Journal ArticleDOI
Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0
Laurent Heirendt,Sylvain Arreckx,Thomas Pfau,Sebastián N. Mendoza,Anne Richelle,Almut Heinken,Hulda S. Haraldsdóttir,Jacek Wachowiak,Sarah M. Keating,Vanja Vlasov,Stefania Magnusdottir,Chiam Yu Ng,German Preciat,Alise Žagare,Siu Hung Joshua Chan,Maike K. Aurich,Catherine M. Clancy,Jennifer Modamio,John T. Sauls,Alberto Noronha,Aarash Bordbar,Benjamin Cousins,Diana C. El Assal,Luis Vitores Valcárcel,Iñigo Apaolaza,Susan Ghaderi,Masoud Ahookhosh,Marouen Ben Guebila,Andrejs Kostromins,Nicolas Sompairac,Hoai M. Le,Ding Ma,Yuekai Sun,Lin Wang,James T. Yurkovich,Miguel A.P. Oliveira,Phan Tu Vuong,Lemmer P. El Assal,Inna Kuperstein,Andrei Zinovyev,H. Scott Hinton,William A. Bryant,Francisco J. Aragón Artacho,Francisco J. Planes,Egils Stalidzans,Alejandro Maass,Santosh Vempala,Michael Hucka,Michael A. Saunders,Costas D. Maranas,Nathan E. Lewis,Thomas Sauter,Bernhard O. Palsson,Bernhard O. Palsson,Ines Thiele,Ronan M. T. Fleming,Ronan M. T. Fleming +56 more
TL;DR: This protocol provides an overview of all new features of the COBRA Toolbox and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios.
Journal ArticleDOI
Computing the shortest elementary flux modes in genome-scale metabolic networks
Luis F. de Figueiredo,Adam Podhorski,Angel Rubio,Christoph Kaleta,John E. Beasley,Stefan Schuster,Francisco J. Planes +6 more
TL;DR: A novel procedure to efficiently determine the K-shortest EFMs in large-scale metabolic networks is presented, finding that glucose catabolism, ammonium assimilation, lysine anabolism and cofactor balancing were correctly predicted.
Posted Content
Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0.
Laurent Heirendt,Sylvain Arreckx,Thomas Pfau,Sebastián N. Mendoza,Anne Richelle,Almut Heinken,Hulda S. Haraldsdóttir,Jacek Wachowiak,Sarah M. Keating,Vanja Vlasov,Stefania Magnusdottir,Chiam Yu Ng,German Preciat,Alise Žagare,Siu Hung Joshua Chan,Maike K. Aurich,Catherine M. Clancy,Jennifer Modamio,John T. Sauls,Alberto Noronha,Aarash Bordbar,Benjamin Cousins,Diana C. El Assal,Luis Vitores Valcárcel,Iñigo Apaolaza,Susan Ghaderi,Masoud Ahookhosh,Marouen Ben Guebila,Andrejs Kostromins,Nicolas Sompairac,Hoai M. Le,Ding Ma,Yuekai Sun,Lin Wang,James T. Yurkovich,Miguel A.P. Oliveira,Phan Tu Vuong,Lemmer P. El Assal,Inna Kuperstein,Andrei Zinovyev,H. Scott Hinton,William A. Bryant,Francisco J. Aragón Artacho,Francisco J. Planes,Egils Stalidzans,Alejandro Maass,Santosh Vempala,Michael Hucka,Michael A. Saunders,Costas D. Maranas,Nathan E. Lewis,Thomas Sauter,Bernhard O. Palsson,Ines Thiele,Ronan M. T. Fleming +54 more
TL;DR: This protocol can be adapted for the generation and analysis of a constraint-based model in a wide variety of molecular systems biology scenarios and is an update to the COBRA Toolbox 1.0 and 2.0.
Journal ArticleDOI
Joint analysis of miRNA and mRNA expression data
TL;DR: These methods that combine both expression and sequence-based putative targets to predict miRNA targets are reviewed.
Journal ArticleDOI
CANCERTOOL: A Visualization and Representation Interface to Exploit Cancer Datasets.
Ana R. Cortazar,Verónica Torrano,Natalia Martín-Martín,Alfredo Caro-Maldonado,Laura Camacho,Ivana Hermanova,Elizabeth Guruceaga,Luis Francisco Lorenzo-Martín,Ruben Caloto,Roger R. Gomis,Iñigo Apaolaza,Víctor Quesada,Jan Trka,Antonio Gómez-Muñoz,Silvestre Vincent,Xosé R. Bustelo,Francisco J. Planes,Ana M. Aransay,Arkaitz Carracedo +18 more
TL;DR: CERTOOL is a web-based interface that aims to overcome the major limitations of public transcriptomics dataset analysis for highly prevalent types of cancer and provides rapid and comprehensive visualization of gene expression data for the gene(s) of interest in well-annotated cancer datasets.