Edinburgh Research Explorer Next-Generation Global Biomonitoring
暂无分享,去创建一个
David A. Bohan | G. Woodward | Alireza Tamaddoni-Nezhad | D. Bohan | C. Vacher | A. Raybould | A. Dumbrell | Guy Woodward | Corinne Vacher | Alan Raybould
[1] Michael J. O. Pocock,et al. The Robustness and Restoration of a Network of Ecological Networks , 2012, Science.
[2] Carlos Garbisu,et al. Multi-targeted metagenetic analysis of the influence of climate and environmental parameters on soil microbial communities along an elevational gradient , 2016, Scientific Reports.
[3] Stephen Muggleton,et al. Meta-interpretive learning: application to grammatical inference , 2013, Machine Learning.
[4] R. Solé,et al. Ecological networks and their fragility , 2006, Nature.
[5] Eske Willerslev,et al. Environmental DNA - An emerging tool in conservation for monitoring past and present biodiversity , 2015 .
[6] D. Raffaelli,et al. Food Webs, Body Size and the Curse of the Latin Binomial , 2007 .
[7] Gunnar Rätsch,et al. Ecological Modeling from Time-Series Inference: Insight into Dynamics and Stability of Intestinal Microbiota , 2013, PLoS Comput. Biol..
[8] Craig W. Osenberg,et al. Detection of Environmental Impacts: Natural Variability, Effect Size, and Power Analysis , 1994 .
[9] Stephen Muggleton,et al. Automated Discovery of Food Webs from Ecological Data Using Logic-Based Machine Learning , 2011, PloS one.
[10] J. Karr. Assessment of Biotic Integrity Using Fish Communities , 1981 .
[11] Loïc Schwaller,et al. Deciphering the Pathobiome: Intra- and Interkingdom Interactions Involving the Pathogen Erysiphe alphitoides , 2016, Microbial Ecology.
[12] Karoline Faust,et al. Metagenomics meets time series analysis: unraveling microbial community dynamics. , 2015, Current opinion in microbiology.
[13] J. Gilbert,et al. Metagenomics - a guide from sampling to data analysis , 2012, Microbial Informatics and Experimentation.
[14] Corinne Whitby,et al. Importance and controls of anaerobic ammonium oxidation influenced by riverbed geology , 2016 .
[15] R. Henrik Nilsson,et al. Tidying Up International Nucleotide Sequence Databases: Ecological, Geographical and Sequence Quality Annotation of ITS Sequences of Mycorrhizal Fungi , 2011, PloS one.
[16] D. Haydon,et al. Alternative stable states in ecology , 2003 .
[17] Stephen Muggleton,et al. Theory Completion Using Inverse Entailment , 2000, ILP.
[18] David B. Dunson,et al. Using latent variable models to identify large networks of species‐to‐species associations at different spatial scales , 2016 .
[19] Jens O. Riede,et al. Long-Term Dynamics of a Well-Characterised Food Web , 2011 .
[20] Jonathan Friedman,et al. Inferring Correlation Networks from Genomic Survey Data , 2012, PLoS Comput. Biol..
[21] Vanni Bucci,et al. MDSINE: Microbial Dynamical Systems INference Engine for microbiome time-series analyses , 2016, Genome Biology.
[22] Matthew A. Barnes,et al. The ecology of environmental DNA and implications for conservation genetics , 2016, Conservation Genetics.
[23] David A. Bohan,et al. Invertebrate responses to the management of genetically modified herbicide-tolerant and conventional spring crops. II. Within-field epigeal and aerial arthropods. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[24] Corinne Whitby,et al. Nitrate Reduction Functional Genes and Nitrate Reduction Potentials Persist in Deeper Estuarine Sediments. Why? , 2014, PloS one.
[25] Stephen Muggleton,et al. Towards Machine Learning of Predictive Models from Ecological Data , 2014, ILP.
[26] L. Fraissinet-Tachet,et al. PCR Primers to Study the Diversity of Expressed Fungal Genes Encoding Lignocellulolytic Enzymes in Soils Using High-Throughput Sequencing , 2014, PloS one.
[27] Xin Zhou,et al. Networking Our Way to Better Ecosystem Service Provision. , 2016, Trends in ecology & evolution.
[28] D. Niemeijer. Developing indicators for environmental policy: data-driven and theory-driven approaches examined by example , 2002 .
[29] Neo D. Martinez,et al. Food webs: reconciling the structure and function of biodiversity. , 2012, Trends in ecology & evolution.
[30] Stephen Muggleton,et al. Machine Learning a Probabilistic Network of Ecological Interactions , 2011, ILP.
[31] Owen L. Petchey,et al. Individual-Based Food Webs , 2010 .
[32] Daniel H. Buckley,et al. A Comprehensive Evaluation of PCR Primers to Amplify the nifH Gene of Nitrogenase , 2012, PloS one.
[33] William A. Walters,et al. QIIME allows analysis of high-throughput community sequencing data , 2010, Nature Methods.
[34] David A. Matthews,et al. Real-time, portable genome sequencing for Ebola surveillance , 2016, Nature.
[35] Alex J. Dumbrell,et al. What Goes in Must Come out: Testing for Biases in Molecular Analysis of Arbuscular Mycorrhizal Fungal Communities , 2014, PloS one.
[36] John M. Holland,et al. Intraguild predation in winter wheat: prey choice by a common epigeal carabid consuming spiders , 2013 .
[37] Alex J. Dumbrell,et al. Microbial Community Analysis by Single-Amplicon High-Throughput Next Generation Sequencing: Data Analysis – From Raw Output to Ecology , 2016 .
[38] Julia L. Blanchard,et al. Climate change: A rewired food web , 2015, Nature.
[39] Niranjan Nagarajan,et al. Predicting microbial interactions through computational approaches. , 2016, Methods.
[40] Guadalupe Peralta,et al. Apparent competition drives community-wide parasitism rates and changes in host abundance across ecosystem boundaries , 2016, Nature Communications.
[41] Peer Bork,et al. Determinants of community structure in the global plankton interactome , 2015, Science.
[42] Daniel E. Schindler,et al. TROPHIC CASCADES, NUTRIENTS, AND LAKE PRODUCTIVITY: WHOLE‐LAKE EXPERIMENTS , 2001 .
[43] Dominique Gravel,et al. A theory for species co-occurrence in interaction networks , 2015, Theoretical Ecology.
[44] Owen L Petchey,et al. Size, foraging, and food web structure , 2008, Proceedings of the National Academy of Sciences.
[45] Christopher H. Bryant,et al. Functional genomic hypothesis generation and experimentation by a robot scientist , 2004, Nature.
[46] Jeffery H. Fenton,et al. A miniature integrated device for automated multistep genetic assays. , 2000, Nucleic acids research.
[47] Robert C. Edgar,et al. UPARSE: highly accurate OTU sequences from microbial amplicon reads , 2013, Nature Methods.
[48] Dirk Husmeier,et al. Inferring species interaction networks from species abundance data: A comparative evaluation of various statistical and machine learning methods , 2010, Ecol. Informatics.
[49] Stanley T. Asah,et al. The IPBES Conceptual Framework - connecting nature and people , 2015 .
[50] R. Danovaro,et al. Metagenetic tools for the census of marine meiofaunal biodiversity: An overview. , 2015, Marine genomics.
[51] Christian L. Müller,et al. Sparse and Compositionally Robust Inference of Microbial Ecological Networks , 2014, PLoS Comput. Biol..
[52] Rita Sipos,et al. Effect of primer mismatch, annealing temperature and PCR cycle number on 16S rRNA gene-targetting bacterial community analysis. , 2007, FEMS microbiology ecology.
[53] Sophie J. Weiss,et al. Correlation detection strategies in microbial data sets vary widely in sensitivity and precision , 2016, The ISME Journal.
[54] John G Kenny,et al. A comprehensive benchmarking study of protocols and sequencing platforms for 16S rRNA community profiling , 2016, BMC Genomics.
[55] Karl Auerswald,et al. Effects of functional diversity loss on ecosystem functions are influenced by compensation. , 2016, Ecology.
[56] Eve McDonald-Madden,et al. Operationalizing Network Theory for Ecosystem Service Assessments. , 2017, Trends in ecology & evolution.
[57] Juan M Morales,et al. Invasive Mutualists Erode Native Pollination Webs , 2008, PLoS biology.
[58] Corinne Whitby,et al. amoA Gene Abundances and Nitrification Potential Rates Suggest that Benthic Ammonia-Oxidizing Bacteria and Not Archaea Dominate N Cycling in the Colne Estuary, United Kingdom , 2014, Applied and Environmental Microbiology.
[59] Borut Smodiš,et al. Biomonitoring of air pollution as exemplified by recent IAEA programs , 2007, Biological Trace Element Research.
[60] Alireza Tamaddoni-Nezhad,et al. Learning ecological networks from next-generation sequencing data , 2016 .
[61] Stephen Muggleton,et al. Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited , 2013, Machine Learning.
[62] Rui Camacho,et al. Inductive Logic Programming , 2004, Lecture Notes in Computer Science.
[63] Stephen Muggleton,et al. Application of abductive ILP to learning metabolic network inhibition from temporal data , 2006, Machine Learning.
[64] Thomas Bell,et al. Gene-to-ecosystem impacts of a catastrophic pesticide spill: testing a multilevel bioassessment approach in a river ecosystem , 2016 .
[65] Martin F. Polz,et al. Bias in Template-to-Product Ratios in Multitemplate PCR , 1998, Applied and Environmental Microbiology.
[66] Michael J. O. Pocock,et al. Merging DNA metabarcoding and ecological network analysis to understand and build resilient terrestrial ecosystems , 2016 .
[67] Cathy Hawes,et al. Effects on weed and invertebrate abundance and diversity of herbicide management in genetically modified herbicide-tolerant winter-sown oilseed rape , 2005, Proceedings of the Royal Society B: Biological Sciences.
[68] Christian Bockstaller,et al. Indicators: Tools to Evaluate the Environmental Impacts of Farming Systems , 1999 .
[69] S. Carpenter,et al. Catastrophic shifts in ecosystems , 2001, Nature.