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Andrej Aderhold
Researcher at University of Glasgow
Publications - 17
Citations - 1642
Andrej Aderhold is an academic researcher from University of Glasgow. The author has contributed to research in topics: Inference & Bayesian linear regression. The author has an hindex of 6, co-authored 16 publications receiving 1458 citations. Previous affiliations of Andrej Aderhold include Universidade Federal do Rio Grande do Sul & University of St Andrews.
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Wisdom of crowds for robust gene network inference
Daniel Marbach,James C. Costello,Robert Küffner,Nicole M. Vega,Robert J. Prill,Diogo M. Camacho,Kyle R. Allison,Andrej Aderhold,Richard Bonneau,Yukun Chen,James J. Collins,Francesca Cordero,Martin Crane,Frank Dondelinger,Mathias Drton,Roberto Esposito,Rina Foygel,Alberto de la Fuente,Jan Gertheiss,Pierre Geurts,Alex Greenfield,Marco Grzegorczyk,Anne-Claire Haury,Benjamin Holmes,Torsten Hothorn,Dirk Husmeier,Vân Anh Huynh-Thu,Alexandre Irrthum,Manolis Kellis,Guy Karlebach,Sophie Lèbre,Vincenzo De Leo,Aviv Madar,Subramani Mani,Fantine Mordelet,Harry Ostrer,Zhengyu Ouyang,Ravi Pandya,Tobias Petri,Andrea Pinna,Christopher S. Poultney,Serena Rezny,Heather J. Ruskin,Yvan Saeys,Ron Shamir,Alina Sîrbu,Mingzhou Song,Nicola Soranzo,Alexander Statnikov,Gustavo Stolovitzky,Nicci Vega,Paola Vera-Licona,Jean-Philippe Vert,Alessia Visconti,Haizhou Wang,Louis Wehenkel,Lukas Windhager,Yang Zhang,Ralf Zimmer +58 more
TL;DR: A comprehensive blind assessment of over 30 network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae and in silico microarray data defines the performance, data requirements and inherent biases of different inference approaches, and provides guidelines for algorithm application and development.
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Performance evaluation of artificial bee colony optimization and new selection schemes
TL;DR: The influence of ABC’s parameters on its optimization behavior is studied in detail and two new variants of ABC are proposed which use new methods for the position update of the artificial bees.
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Changes and classification in myocardial contractile function in the left ventricle following acute myocardial infarction
TL;DR: It is shown, for the first time, that compared with healthy controls, patients with STEMI exhibited increased LV wall active tension when normalized by systolic blood pressure, which suggests an increased demand on the contractile reserve of remote functional myocardium.
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Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data
TL;DR: A novel Bayesian regression and multiplechan- gepoint model (BRAM) for reconstructing species interaction networks from observed species distributions is devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity.
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Statistical inference of regulatory networks for circadian regulation.
TL;DR: This study provides relative network reconstruction accuracy scores for a critical comparative performance evaluation, suggests new hypotheses about the structure of the central circadian gene regulatory network in A. thaliana, and quantifies the influence of systematically missing values related to unknown protein concentrations and mRNA transcription rates.