-
Notifications
You must be signed in to change notification settings - Fork 2
/
co-occurrence_vignette.bib
124 lines (114 loc) · 10.6 KB
/
co-occurrence_vignette.bib
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
@article{ono_cyrest:_2015,
title = {{CyREST}: {Turbocharging} {Cytoscape} {Access} for {External} {Tools} via a {RESTful} {API} [version 1; referees: 2 approved]},
volume = {4},
doi = {10.12688/f1000research.6767.1},
number = {478},
journal = {F1000Research},
author = {Ono, K and Muetze, T and Kolishovski, G and Shannon, P and Demchak, B},
year = {2015}
}
@article{brum_patterns_2015,
title = {Patterns and ecological drivers of ocean viral communities},
volume = {348},
url = {http://www.sciencemag.org/content/348/6237/1261498.short},
number = {6237},
urldate = {2015-07-12},
journal = {Science},
author = {Brum, Jennifer R. and Ignacio-Espinoza, J. Cesar and Roux, Simon and Doulcier, Guilhem and Acinas, Silvia G. and Alberti, Adriana and Chaffron, Samuel and Cruaud, Corinne and de Vargas, Colomban and Gasol, Josep M. and {others}},
year = {2015},
pages = {1261498},
file = {Brum et al. - 2015 - Patterns and ecological drivers of ocean viral com.pdf:/media/Windows7_OS/Users/julia_lenovo/AppData/Roaming/Zotero/Zotero/Profiles/dx5oed4z.default/zotero/storage/HB4RDWPC/Brum et al. - 2015 - Patterns and ecological drivers of ocean viral com.pdf:application/pdf;Science-2015-Brum-.pdf:/media/Windows7_OS/Users/julia_lenovo/AppData/Roaming/Zotero/Zotero/Profiles/dx5oed4z.default/zotero/storage/ZI6WSGQ2/Science-2015-Brum-.pdf:application/pdf}
}
@article{sunagawa_structure_2015,
title = {Structure and function of the global ocean microbiome},
volume = {348},
url = {http://www.sciencemag.org/content/348/6237/1261359.short},
number = {6237},
urldate = {2015-07-12},
journal = {Science},
author = {Sunagawa, Shinichi and Coelho, Luis Pedro and Chaffron, Samuel and Kultima, Jens Roat and Labadie, Karine and Salazar, Guillem and Djahanschiri, Bardya and Zeller, Georg and Mende, Daniel R. and Alberti, Adriana and {others}},
year = {2015},
pages = {1261359},
file = {Sunagawa et al. - 2015 - Structure and function of the global ocean microbi.pdf:/media/Windows7_OS/Users/julia_lenovo/AppData/Roaming/Zotero/Zotero/Profiles/dx5oed4z.default/zotero/storage/GJPZK55G/Sunagawa et al. - 2015 - Structure and function of the global ocean microbi.pdf:application/pdf}
}
@article{csardi_igraph_2006,
title = {The igraph software package for complex network research},
volume = {Complex Systems},
url = {http://igraph.org},
journal = {InterJournal},
author = {Csardi, Gabor and Nepusz, Tamas},
year = {2006},
pages = {1695}
}
@article{venter_environmental_2004,
title = {Environmental genome shotgun sequencing of the {Sargasso} {Sea}},
volume = {304},
url = {http://science.sciencemag.org/content/304/5667/66.abstract},
doi = {10.1126/science.1093857},
abstract = {We have applied “whole-genome shotgun sequencing” to microbial populations collected en masse on tangential flow and impact filters from seawater samples collected from the Sargasso Sea near Bermuda. A total of 1.045 billion base pairs of nonredundant sequence was generated, annotated, and analyzed to elucidate the gene content, diversity, and relative abundance of the organisms within these environmental samples. These data are estimated to derive from at least 1800 genomic species based on sequence relatedness, including 148 previously unknown bacterial phylotypes. We have identified over 1.2 million previously unknown genes represented in these samples, including more than 782 new rhodopsin-like photoreceptors. Variation in species present and stoichiometry suggests substantial oceanic microbial diversity.},
number = {5667},
journal = {Science},
author = {Venter, J. Craig and Remington, Karin and Heidelberg, John F. and Halpern, Aaron L. and Rusch, Doug and Eisen, Jonathan A. and Wu, Dongying and Paulsen, Ian and Nelson, Karen E. and Nelson, William and Fouts, Derrick E. and Levy, Samuel and Knap, Anthony H. and Lomas, Michael W. and Nealson, Ken and White, Owen and Peterson, Jeremy and Hoffman, Jeff and Parsons, Rachel and Baden-Tillson, Holly and Pfannkoch, Cynthia and Rogers, Yu-Hui and Smith, Hamilton O.},
month = apr,
year = {2004},
pages = {66--74},
file = {Venter et al. - 2004 - Science (New York, N.Y.).pdf:/media/Windows7_OS/Users/julia_lenovo/AppData/Roaming/Zotero/Zotero/Profiles/dx5oed4z.default/zotero/storage/RNPG64TM/Venter et al. - 2004 - Science (New York, N.Y.).pdf:application/pdf;Venter et al. - 2007 - Unknown.pdf:/media/Windows7_OS/Users/julia_lenovo/AppData/Roaming/Zotero/Zotero/Profiles/dx5oed4z.default/zotero/storage/IPHBAIA7/Venter et al. - 2007 - Unknown.pdf:application/pdf}
}
@article{weiss_correlation_2016,
title = {Correlation detection strategies in microbial data sets vary widely in sensitivity and precision},
volume = {10},
issn = {1751-7362},
url = {http://dx.doi.org/10.1038/ismej.2015.235},
abstract = {Disruption of healthy microbial communities has been linked to numerous diseases, yet microbial interactions are little understood. This is due in part to the large number of bacteria, and the much larger number of interactions (easily in the millions), making experimental investigation very difficult at best and necessitating the nascent field of computational exploration through microbial correlation networks. We benchmark the performance of eight correlation techniques on simulated and real data in response to challenges specific to microbiome studies: fractional sampling of ribosomal RNA sequences, uneven sampling depths, rare microbes and a high proportion of zero counts. Also tested is the ability to distinguish signals from noise, and detect a range of ecological and time-series relationships. Finally, we provide specific recommendations for correlation technique usage. Although some methods perform better than others, there is still considerable need for improvement in current techniques.},
number = {7},
journal = {ISME J},
author = {Weiss, Sophie and Van Treuren, Will and Lozupone, Catherine and Faust, Karoline and Friedman, Jonathan and Deng, Ye and Xia, Li Charlie and Xu, Zhenjiang Zech and Ursell, Luke and Alm, Eric J and Birmingham, Amanda and Cram, Jacob A and Fuhrman, Jed A and Raes, Jeroen and Sun, Fengzhu and Zhou, Jizhong and Knight, Rob},
month = jul,
year = {2016},
pages = {1669--1681}
}
@article{shannon_cytoscape:_2003,
title = {Cytoscape: a software environment for integrated models of biomolecular interaction networks},
volume = {13},
shorttitle = {Cytoscape},
url = {http://genome.cshlp.org/content/13/11/2498.short},
number = {11},
urldate = {2016-07-14},
journal = {Genome research},
author = {Shannon, Paul and Markiel, Andrew and Ozier, Owen and Baliga, Nitin S. and Wang, Jonathan T. and Ramage, Daniel and Amin, Nada and Schwikowski, Benno and Ideker, Trey},
year = {2003},
pages = {2498--2504},
file = {Genome Res.-2003-Shannon-2498-504.pdf:/media/Windows7_OS/Users/julia_lenovo/AppData/Roaming/Zotero/Zotero/Profiles/dx5oed4z.default/zotero/storage/3NHH6UTD/Genome Res.-2003-Shannon-2498-504.pdf:application/pdf}
}
@article{lima-mendez_determinants_2015,
title = {Determinants of community structure in the global plankton interactome},
volume = {348},
url = {http://science.sciencemag.org/content/348/6237/1262073.abstract},
doi = {10.1126/science.1262073},
abstract = {Species interaction networks are shaped by abiotic and biotic factors. Here, as part of the Tara Oceans project, we studied the photic zone interactome using environmental factors and organismal abundance profiles and found that environmental factors are incomplete predictors of community structure. We found associations across plankton functional types and phylogenetic groups to be nonrandomly distributed on the network and driven by both local and global patterns. We identified interactions among grazers, primary producers, viruses, and (mainly parasitic) symbionts and validated network-generated hypotheses using microscopy to confirm symbiotic relationships. We have thus provided a resource to support further research on ocean food webs and integrating biological components into ocean models.},
number = {6237},
journal = {Science},
author = {Lima-Mendez, Gipsi and Faust, Karoline and Henry, Nicolas and Decelle, Johan and Colin, Sébastien and Carcillo, Fabrizio and Chaffron, Samuel and Ignacio-Espinosa, J. Cesar and Roux, Simon and Vincent, Flora and Bittner, Lucie and Darzi, Youssef and Wang, Jun and Audic, Stéphane and Berline, Léo and Bontempi, Gianluca and Cabello, Ana M. and Coppola, Laurent and Cornejo-Castillo, Francisco M. and d'Ovidio, Francesco and De Meester, Luc and Ferrera, Isabel and Garet-Delmas, Marie-José and Guidi, Lionel and Lara, Elena and Pesant, Stéphane and Royo-Llonch, Marta and Salazar, Guillem and Sánchez, Pablo and Sebastian, Marta and Souffreau, Caroline and Dimier, Céline and Picheral, Marc and Searson, Sarah and Kandels-Lewis, Stefanie and Gorsky, Gabriel and Not, Fabrice and Ogata, Hiroyuki and Speich, Sabrina and Stemmann, Lars and Weissenbach, Jean and Wincker, Patrick and Acinas, Silvia G. and Sunagawa, Shinichi and Bork, Peer and Sullivan, Matthew B. and Karsenti, Eric and Bowler, Chris and de Vargas, Colomban and Raes, Jeroen},
month = may,
year = {2015},
file = {Ignacio-Espinosa et al. - 2015 - Determinants of community structure in the global .pdf:/media/Windows7_OS/Users/julia_lenovo/AppData/Roaming/Zotero/Zotero/Profiles/dx5oed4z.default/zotero/storage/ESUQB74R/Ignacio-Espinosa et al. - 2015 - Determinants of community structure in the global .pdf:application/pdf;Ignacio-Espinosa et al. - 2015 - Determinants of community structure in the global .pdf:/media/Windows7_OS/Users/julia_lenovo/AppData/Roaming/Zotero/Zotero/Profiles/dx5oed4z.default/zotero/storage/QJ5DGNFS/Ignacio-Espinosa et al. - 2015 - Determinants of community structure in the global .pdf:application/pdf}
}
@article{shannon_rcytoscape:_2013,
title = {{RCytoscape}: tools for exploratory network analysis},
volume = {14},
issn = {1471-2105},
url = {http://dx.doi.org/10.1186/1471-2105-14-217},
doi = {10.1186/1471-2105-14-217},
abstract = {Biomolecular pathways and networks are dynamic and complex, and the perturbations to them which cause disease are often multiple, heterogeneous and contingent. Pathway and network visualizations, rendered on a computer or published on paper, however, tend to be static, lacking in detail, and ill-equipped to explore the variety and quantities of data available today, and the complex causes we seek to understand.},
number = {1},
journal = {BMC Bioinformatics},
author = {Shannon, Paul T. and Grimes, Mark and Kutlu, Burak and Bot, Jan J. and Galas, David J.},
year = {2013},
pages = {1--9}
}
@book{gentleman_graph:_2016,
title = {graph: graph: {A} package to handle graph data structures},
author = {Gentleman, R. and Whalen, Elizabeth and Huber, W. and Falcon, S.},
year = {2016},
note = {R package version 1.50.0}
}