Name Description Type Download
NYClimateMarch2014

We consider different types of social relationships amoung users, obtained from Twitter during an exceptional event. In this specific dataset we focused on People's Climate March in 2014.
The multiplex network used in the paper makes use of 3 layers, corresponding to retweet, mentions and replies observed between:
Start: 2014-09-19 00:46:19
End: 2014-09-22 06:56:25

Ref: E. Omodei, M. De Domenico, A. Arenas. - Characterizing interactions in online social networks during exceptional events.. Front. Phys. 3, 59 (2015)

Files format: layerID nodeID nodeID weight

3 layers Multiplex

Nodes: 102439

Edges: 353495
Social
Temporal Multiplex
Directed
Weighted
Cannes2013

We consider different types of social relationships amoung users, obtained from Twitter during an exceptional event. In this specific dataset we focused on Cannes Film Festival in 2013.
The multiplex network used in the paper makes use of 3 layers, corresponding to retweet, mentions and replies observed between:
Start: 2013-05-06 07:23:49
End: 2013-06-03 05:48:26

Ref: E. Omodei, M. De Domenico, A. Arenas. - Characterizing interactions in online social networks during exceptional events.. Front. Phys. 3, 59 (2015)

Files format: layerID nodeID nodeID weight

3 layers Multiplex

Nodes: 438537

Edges: 991854
Social
Temporal Multiplex
Directed
Weighted
MoscowAthletics2013

We consider different types of social relationships amoung users, obtained from Twitter during an exceptional event. In this specific dataset we focused on 2013 World Championships in Athletics.
The multiplex network used in the paper makes use of 3 layers, corresponding to retweet, mentions and replies observed between:
Start: 2013-08-05 11:25:46
End: 2013-08-19 14:35:21

Ref: E. Omodei, M. De Domenico, A. Arenas. - Characterizing interactions in online social networks during exceptional events.. Front. Phys. 3, 59 (2015)

Files format: layerID nodeID nodeID weight

3 layers Multiplex

Nodes: 88804

Edges: 210250
Social
Temporal Multiplex
Directed
Weighted
MLKing2013

We consider different types of social relationships amoung users, obtained from Twitter during an exceptional event. In this specific dataset we focused on 50th aniversary of Marthin Luther King's speech "I have a dream..." in 2013.
The multiplex network used in the paper makes use of 3 layers, corresponding to retweet, mentions and replies observed between:
Start: 2013-08-25 15:41:36
End: 2013-09-02 10:16:21

Ref: E. Omodei, M. De Domenico, A. Arenas. - Characterizing interactions in online social networks during exceptional events.. Front. Phys. 3, 59 (2015)

Files format: layerID nodeID nodeID weight

3 layers Multiplex

Nodes: 327707

Edges: 396671
Social
Temporal Multiplex
Directed
Weighted
ObamaInIsrael2013

We consider different types of social relationships amoung users, obtained from Twitter during an exceptional event. In this specific dataset we focused on a visit to Israel by US President Barack Obama in 2013
The multiplex network used in the paper makes use of 3 layers, corresponding to retweet, mentions and replies observed between:
Start: 2013-03-19 16:56:29
End: 2013-04-03 23:24:34

Ref: E. Omodei, M. De Domenico, A. Arenas. - Characterizing interactions in online social networks during exceptional events.. Front. Phys. 3, 59 (2015)

Files format: layerID nodeID nodeID weight

3 layers Multiplex

Nodes: 2281259

Edges: 4061960
Social
Temporal Multiplex
Directed
Weighted
ECCS2013 Day-by-day interactions over Twitter between people attending the ECCS 2013 conference in Barcelona.
This is a time-varying multiplex network, with two layers corresponding to two different actions: mentioning and retweeting.
See more details in the webpage dedicated to ECCS 2013
Social
Temporal Multiplex
Directed
Weighted
Soon...
HIGGS TWITTER The Higgs dataset has been built after monitoring the spreading processes on Twitter before, during and after the announcement of the discovery of a new particle with the features of the elusive Higgs boson on 4th July 2012. The messages posted in Twitter about this discovery between 1st and 7th July 2012 are considered.

Ref: M. De Domenico, A. Lima, P. Mougel and M. Musolesi. The Anatomy of a Scientific Rumor. (Nature Open Access) Scientific Reports 3, 2980 (2013).
Friends/follower graph

Nodes: 456631
Edges: 14855875
Social
Monoplex
Directed
Graph of who retweets whom

Nodes: 425008
Edges: 733647
Social
Monoplex
Directed
Weighted
Graph of who replies to who

Nodes: 37366
Edges: 30836
Social
Monoplex
Directed
Weighted
Graph of who mentions whom

Nodes: 302975
Edges: 449827
Social
Monoplex
Directed
Weighted
HIGGS MULTIPLEX Multiplex of social interactions in Twitter corresponding to the different actions (friendship, replying, mentioning and retweeting) monitored in the Higgs dataset (see above)
There are two multiplex networks: 1) two layers, friendship and aggregated interactions, respectively; 2) four layers, friendship and each type of interaction in each layer separately. See more details in the webpage dedicated to Higgs Rumor

Ref: M. De Domenico, A. Lima, P. Mougel and M. Musolesi The Anatomy of a Scientific Rumor. (Nature Open Access) Scientific Reports 3, 2980 (2013).

Files format: layerID nodeID nodeID weight
2-layers Multiplex

Nodes: 456631
Social
Multiplex
Directed
Weighted
4-layers Multiplex

Nodes: 456631
Social
Multiplex
Directed
Weighted
LONDON MULTIPLEX TRANSPORT NETWORK

Data was collected in 2013 from the official website of Transport for London ( https://www.tfl.gov.uk/) and manually cross-checked.

Nodes are train stations in London and edges encode existing routes between stations. Underground, Overground and DLR stations are considered (see https://www.tfl.gov.uk/ for further details). The multiplex network used in the paper makes use of three layers corresponding to:

  1. The aggregation to a single weighted graph of the networks of stations corresponding to each underground line (e.g., District, Circle, etc)
  2. The network of stations connected by Overground
  3. The network of stations connected by DLR

Raw data and geographical coordinates of stations are provided. We also provide the multiplex networks after considering real disruptions occurring in London.

Ref: Manlio De Domenico, Albert Solé-Ribalta, Sergio Gómez, and Alex Arenas, Navigability of interconnected networks under random failures. PNAS 111, 8351-8356 (2014)


Files format: layerID nodeID nodeID weight
[3 | 13] - layers Multiplex

Nodes: 369

Edges: 441(503)
Transport
Multiplex
Undirected
Weighted
EU-AIR TRANSPORTATION MULTIPLEX

The multilayer network is composed by thirty-seven different layers each one corresponding to a different airline operating in Europe.

Ref: Alessio Cardillo, Jesús Gómez-Gardenes, Massimiliano Zanin, Miguel Romance, David Papo, Francisco del Pozo and Stefano Boccaletti - Emergence of network features from multiplexity. Scientific Reports 3, Article number: 1344 doi:10.1038/srep01344

See the official web page for further details.


Files format: layerID nodeID nodeID weight
37 layers Multiplex

Nodes: 450

Edges: 3588
Transport
Multiplex
Undirected
Unweighted
CS-AARHUS

The multiplex social network consists of five kinds of online and offline relationships (Facebook, Leisure, Work, Co-authorship, Lunch) between the employees of Computer Science department at Aarhus.

Ref: Matteo Magnani, Barbora Micenkova, Luca Rossi - Combinatorial Analysis of Multiple Networks. arXiv:1303.4986 (2013)

See the official web page for further details.


Files format: layerID nodeID nodeID weight
5 layers Multiplex

Nodes: 61

Edges: 620
Social
Multiplex
Undirected
Unweighted
CKM PHYSICIANS INNOVATION

Data collected by Coleman, Katz and Menzel on medical innovation, considering physicians in four towns in Illinois, Peoria, Bloomington, Quincy and Galesburg.
They were concerned with the impact of network ties on the physicians' adoption of a new drug, tetracycline. Three sociometric matrices (layers) were generated, based on the following questions:

  1. When you need information or advice about questions of therapy where do you usually turn?
  2. And who are the three or four physicians with whom you most often find yourself discussing cases or therapy in the course of an ordinary week -- last week for instance?
  3. Would you tell me the first names of your three friends whom you see most often socially?

Ref: J. Coleman, E. Katz, and H. Menzel.- "The Diffusion of an Innovation Among Physicians". Sociometry (1957) 20:253-270.


Files format: layerID nodeID nodeID weight
3 layers Multiplex

Nodes: 246

Edges: 1551
Social
Multiplex
Directed
Unweighted
KAPFERER TAILOR SHOP

Interactions in a tailor shop in Zambia (then Northern Rhodesia) over a period of ten months.
Layers represent two different types of interaction, recorded at two different times (seven months apart) over a period of one month. TI1 and TI2 record the "instrumental" (work- and assistance-related) interactions at the two times; TS1 and TS2 the "sociational" (friendship, socioemotional) interactions.
The data are particularly interesting since an abortive strike occurred after the first set of observations, and a successful strike took place after the second.

Ref: Kapferer B. (1972) - "Strategy and transaction in an African factory".


Files format: layerID nodeID nodeID weight
4 layers Multiplex

Nodes: 39

Edges: 1018
Social
Multiplex
Directed
Unweighted
KRACKHARDT HIGH TECH

The multiplex social network consists of 3 kinds of relationships (Advice, Friendship and "Reports to") between managers of a high-tech company.

Ref: D. Krackhardt - "Cognitive social structures". Social Networks (1987), 9, 104-134


Files format: layerID nodeID nodeID weight
3 layers Multiplex

Nodes: 21

Edges: 312
Social
Multiplex
Directed
Unweighted
LAZEGA LAW FIRM

The multiplex social network consists of 3 kinds of (Co-work, Friendship and Advice) between partners and associates of a corporate law partnership.

Ref:Emmanuel Lazega - "The Collegial Phenomenon: The Social Mechanisms of Cooperation Among Peers in a Corporate Law Partnership". Oxford University Press (2001)
Ref: Tom A.B. Snijders, Philippa E. Pattison, Garry L. Robins, and Mark S. Handcock - "New specifications for exponential random graph models". Sociological Methodology (2006), 99-153.


Files format: layerID nodeID nodeID weight
3 layers Multiplex

Nodes: 71

Edges: 2223
Social
Multiplex
Directed
Unweighted
PEDGETT FLORENTINE FAMILIES

The multiplex social network consists of 2 layers (marriage alliances and business relationships) describing florentine families in the Renaissance.

Ref: JF Padgett, CK Ansell - "Robust Action and the Rise of the Medici, 1400-1434". American journal of sociology, 1259-1319 (1993)


Files format: layerID nodeID nodeID weight
2 layers Multiplex

Nodes: 16

Edges: 35
Social
Multiplex
Undirected
Unweighted
VICKERS CHAN 7THGRADERS

The data were collected by Vickers from 29 seventh grade students in a school in Victoria, Australia. Students were asked to nominate their classmates on a number of relations including the following three (layers):

  1. Who do you get on with in the class?
  2. Who are your best friends in the class?
  3. Who would you prefer to work with?
Students 1 through 12 are boys and 13 through 29 are girls.

Ref: M. Vickers and S. Chan - Representing Classroom Social Structure. Melbourne: Victoria Institute of Secondary Education. (1981)


Files format: layerID nodeID nodeID weight
3 layers Multiplex

Nodes: 29

Edges: 740
Social
Multiplex
Directed
Unweighted
C.ELEGANS MULTIPLEX CONNECTOME

Caenorhabditis elegans connectome, where the multiplex consists of layers corresponding to different synaptic junctions: electric ("ElectrJ"), chemical monadic ("MonoSyn"), and polyadic ("PolySyn").
The multiplex network used in the paper makes use of three layers corresponding to:

  1. Electric ("ElectrJ")
  2. Chemical Monadic ("MonoSyn")
  3. Chemical Polyadic ("PolySyn")

Ref: Beth L. Chen, David H. Hall, and Dmitri B. Chklovskii - "Wiring optimization can relate neuronal structure and function" - PNAS 2006 103 (12) 4723–4728

Manlio De Domenico, Mason A. Porter, and Alex Arenas - "MuxViz: A Tool for Multilayer Analysis and Visualization of Networks" - Journal of Complex Networks 2015 3 (2) 159-176


Files format: layerID nodeID nodeID weight
3 layers Multiplex

Nodes: 279

Edges: 5863
Neuronal
Multiplex
Directed
Unweighted
ARABIDOPSIS MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns arabidopsis thaliana.
The multiplex network used in the paper makes use of the following layers:

  1. Direct interaction
  2. Physical association
  3. Additive genetic interaction defined by inequality
  4. Suppressive genetic interaction defined by inequality
  5. Synthetic genetic interaction defined by inequality
  6. Association
  7. Colocalization

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

M. De Domenico, V. Nicosia, A. Arenas, and V. Latora - "Structural reducibility of multilayer networks" - Nature Communications 2015 6, 6864


Files format: layerID nodeID nodeID weight
7 layers Multiplex

Nodes: 6980

Edges: 18654
Genetic
Multiplex
Directed
Unweighted
BOS MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns Bos Linnaeus.
The multiplex network used in the paper makes use of the following layers:

  1. Physical association
  2. Association
  3. Direct interaction
  4. Colocalization

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

M. De Domenico, V. Nicosia, A. Arenas, and V. Latora - "Structural reducibility of multilayer networks" - Nature Communications 2015 6, 6864


Files format: layerID nodeID nodeID weight
4 layers Multiplex

Nodes: 321

Edges: 325
Genetic
Multiplex
Directed
Unweighted
CANDIDA MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns Candida Albicans.
The multiplex network used in the paper makes use of the following layers:

  1. Synthetic genetic interaction defined by inequality
  2. Direct interaction
  3. Suppressive genetic interaction defined by inequality
  4. Additive genetic interaction defined by inequality
  5. Physical association
  6. Association
  7. Colocalization

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

M. De Domenico, V. Nicosia, A. Arenas, and V. Latora - "Structural reducibility of multilayer networks" - Nature Communications 2015 6, 6864


Files format: layerID nodeID nodeID weight
7 layers Multiplex

Nodes: 367

Edges: 397
Genetic
Multiplex
Directed
Unweighted
CELEGANS MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns Caenorhabditis Elegans.
The multiplex network used in the paper makes use of the following layers:

  1. Direct interaction
  2. Physical association
  3. Additive genetic interaction defined by inequality
  4. Suppressive genetic interaction defined by inequality
  5. Association
  6. Colocalization

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

M. De Domenico, V. Nicosia, A. Arenas, and V. Latora - "Structural reducibility of multilayer networks" - Nature Communications 2015 6, 6864


Files format: layerID nodeID nodeID weight
6 layers Multiplex

Nodes: 3879

Edges: 8181
Genetic
Multiplex
Directed
Unweighted
DANIORERIO MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014).
The present folder concerns danio rerio.
The multiplex network used in the paper makes use of the following layers:

  1. Association
  2. Suppressive genetic interaction defined by inequality
  3. Direct interaction
  4. Additive genetic interaction defined by inequality
  5. Physical association

Ref: C. Stark, B.-J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

Manlio De Domenico, Mason A. Porter, and Alex Arenas - "MuxViz: A Tool for Multilayer Analysis and Visualization of Networks" - Journal of Complex Networks 2015 3 (2) 159-176


Files format: layerID nodeID nodeID weight
5 layers Multiplex

Nodes: 155

Edges: 188
Genetic
Multiplex
Directed
Unweighted
DROSOPHILA MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns Drosophila Melanogaster.
The multiplex network used in the paper makes use of the following layers:

  1. Direct interaction
  2. Suppressive genetic interaction defined by inequality
  3. Additive genetic interaction defined by inequality
  4. Physical association
  5. Colocalization
  6. Association
  7. Synthetic genetic interaction defined by inequality

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

M. De Domenico, V. Nicosia, A. Arenas, and V. Latora - "Structural reducibility of multilayer networks" - Nature Communications 2015 6, 6864


Files format: layerID nodeID nodeID weight
7 layers Multiplex

Nodes: 8215

Edges: 43366
Genetic
Multiplex
Directed
Unweighted
GALLUS MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns Gallus Gallus.
The multiplex network used in the paper makes use of the following layers:

  1. Direct interaction
  2. Physical association
  3. Synthetic genetic interaction defined by inequality
  4. Colocalization
  5. Additive genetic interaction defined by inequality
  6. Association

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

M. De Domenico, V. Nicosia, A. Arenas, and V. Latora - "Structural reducibility of multilayer networks" - Nature Communications 2015 6, 6864


Files format: layerID nodeID nodeID weight
6 layers Multiplex

Nodes: 313

Edges: 388
Genetic
Multiplex
Directed
Unweighted
HEPATITUSC MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014).
The multiplex network used in the paper makes use of the following layers:

  1. Physical association
  2. Direct interaction
  3. Colocalization

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

Manlio De Domenico, Mason A. Porter, and Alex Arenas - "MuxViz: A Tool for Multilayer Analysis and Visualization of Networks" - Journal of Complex Networks 2015 3 (2) 159-176


Files format: layerID nodeID nodeID weight
3 layers Multiplex

Nodes: 105

Edges: 137
Genetic
Multiplex
Directed
Unweighted
HOMO MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns homo sapiens.
The multiplex network used in the paper makes use of the following layers:

  1. Direct interaction
  2. Physical association
  3. Suppressive genetic interaction defined by inequality
  4. Association
  5. Colocalization
  6. Additive genetic interaction defined by inequality
  7. Synthetic genetic interaction defined by inequality

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

Manlio De Domenico, Mason A. Porter, and Alex Arenas - "MuxViz: A Tool for Multilayer Analysis and Visualization of Networks" - Journal of Complex Networks 2015 3 (2) 159-176


Files format: layerID nodeID nodeID weight
7 layers Multiplex

Nodes: 18222

Edges: 170899
Genetic
Multiplex
Directed
Unweighted
HUMAN-HERPES4 MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns human herpes virus 4.
The multiplex network used in the paper makes use of the following layers:

  1. Direct interaction
  2. Physical association
  3. Association
  4. Colocalization

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

Manlio De Domenico, Mason A. Porter, and Alex Arenas - "MuxViz: A Tool for Multilayer Analysis and Visualization of Networks" - Journal of Complex Networks 2015 3 (2) 159-176


Files format: layerID nodeID nodeID weight
4 layers Multiplex

Nodes: 216

Edges: 259
Genetic
Multiplex
Directed
Unweighted
HUMAN-HIV1 MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns human HIV type 4.
The multiplex network used in the paper makes use of the following layers:

  1. Physical association
  2. Direct interaction
  3. Colocalization
  4. Association
  5. Suppressive genetic interaction defined by inequality

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

Manlio De Domenico, Mason A. Porter, and Alex Arenas - "MuxViz: A Tool for Multilayer Analysis and Visualization of Networks" - Journal of Complex Networks 2015 3 (2) 159-176


Files format: layerID nodeID nodeID weight
5 layers Multiplex

Nodes: 1005

Edges: 1355
Genetic
Multiplex
Directed
Unweighted
MUS MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns Mus Musculus.
The multiplex network used in the paper makes use of the following layers:

  1. Physical association
  2. Association
  3. Direct interaction
  4. Colocalization
  5. Additive genetic interaction defined by inequality
  6. Synthetic genetic interaction defined by inequality
  7. Suppressive genetic interaction defined by inequality

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

M. De Domenico, V. Nicosia, A. Arenas, and V. Latora - "Structural reducibility of multilayer networks" - Nature Communications 2015 6, 6864


Files format: layerID nodeID nodeID weight
7 layers Multiplex

Nodes: 7747

Edges: 19842
Genetic
Multiplex
Directed
Unweighted
ORYCTOLAGUS MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns homo sapiens.
The multiplex network used in the paper makes use of the following layers:

  1. Direct interaction
  2. Association
  3. Physical association

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

Manlio De Domenico, Mason A. Porter, and Alex Arenas - "MuxViz: A Tool for Multilayer Analysis and Visualization of Networks" - Journal of Complex Networks 2015 3 (2) 159-176


Files format: layerID nodeID nodeID weight
3 layers Multiplex

Nodes: 144

Edges: 144
Genetic
Multiplex
Directed
Unweighted
PLASMODIUM MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns Plasmodium Falciparum.
The multiplex network used in the paper makes use of the following layers:

  1. Direct interaction
  2. Physical association
  3. Association

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

M. De Domenico, V. Nicosia, A. Arenas, and V. Latora - "Structural reducibility of multilayer networks" - Nature Communications 2015 6, 6864


Files format: layerID nodeID nodeID weight
3 layers Multiplex

Nodes: 1023

Edges: 2521
Genetic
Multiplex
Directed
Unweighted
RATTUS MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns Rattus Norvegicus.
The multiplex network used in the paper makes use of the following layers:

  1. Physical association
  2. Direct interaction
  3. Colocalization
  4. Association
  5. Additive genetic interaction defined by inequality
  6. Suppressive genetic interaction defined by inequality

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

M. De Domenico, V. Nicosia, A. Arenas, and V. Latora - "Structural reducibility of multilayer networks" - Nature Communications 2015 6, 6864


Files format: layerID nodeID nodeID weight
6 layers Multiplex

Nodes: 2640

Edges: 4267
Genetic
Multiplex
Directed
Unweighted
SACCHCERE MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns Saccharomyces Cerevisiae.
The multiplex network used in the paper makes use of the following layers:

  1. Physical association
  2. Suppressive genetic interaction defined by inequality
  3. Direct interaction
  4. Synthetic genetic interaction defined by inequality
  5. Association
  6. Colocalization
  7. Additive genetic interaction defined by inequality

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

M. De Domenico, V. Nicosia, A. Arenas, and V. Latora - "Structural reducibility of multilayer networks" - Nature Communications 2015 6, 6864


Files format: layerID nodeID nodeID weight
7 layers Multiplex

Nodes: 6570

Edges: 282754
Genetic
Multiplex
Directed
Unweighted
SACCHPOMB MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns Saccharomyces Pombe.
The multiplex network used in the paper makes use of the following layers:

  1. Direct interaction
  2. Colocalization
  3. Physical association
  4. Suppressive genetic interaction defined by inequality
  5. Synthetic genetic interaction defined by inequality
  6. Additive genetic interaction defined by inequality
  7. Association

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

M. De Domenico, V. Nicosia, A. Arenas, and V. Latora - "Structural reducibility of multilayer networks" - Nature Communications 2015 6, 6864


Files format: layerID nodeID nodeID weight
7 layers Multiplex

Nodes: 4092

Edges: 63676
Genetic
Multiplex
Directed
Unweighted
XENOPUS MULTIPLEX GPI NETWORK

We consider different types of genetic interactions for organisms in the Biological General Repository for Interaction Datasets (BioGRID, thebiogrid.org), a public database that archives and disseminates genetic and protein interaction data from humans and model organisms. BioGRID currently includes more than 720,000 interactions that have been curated from both high-throughput data sets and individual focused studies using over 41,000 publications in the primary literature. We use BioGRID 3.2.108 (updated 1 Jan 2014). The present folder concerns xenopus laevis.
The multiplex network used in the paper makes use of the following layers:

  1. Association
  2. Direct interaction
  3. Physical association
  4. Colocalization
  5. Suppressive genetic interaction defined by inequality

Ref: C. Stark, B. -J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers. - "Biogrid: a general repository for interaction datasets" - Nucleic Acids Research 2006 34 (1) D535–D539

Manlio De Domenico, Mason A. Porter, and Alex Arenas - "MuxViz: A Tool for Multilayer Analysis and Visualization of Networks" - Journal of Complex Networks 2015 3 (2) 159-176


Files format: layerID nodeID nodeID weight
5 layers Multiplex

Nodes: 461

Edges: 620
Genetic
Multiplex
Directed
Unweighted
YEAST LANDSCAPE MULTIPLEX NETWORK

Multiplex in which the layers correspond to interaction networks of genes in Saccharomyces cerevisiae (which was obtained via a synthetic genetic-array methodology) and correlation-based networks in which genes with similar interaction profiles are connected to each other. Positive and negative interactions, as well as positive and negative correlations, are considered.
The multiplex network used in the paper makes use of the following layers:

  1. Positive interactions
  2. Negative interactions
  3. Positive correlations
  4. Negative correlations

Ref: M. Costanzo et al. - "The Genetic Landscape of a Cell" - Science 2010 327 (5964) 425-431

Manlio De Domenico, Mason A. Porter, and Alex Arenas - "MuxViz: A Tool for Multilayer Analysis and Visualization of Networks" - Journal of Complex Networks 2015 3 (2) 159-176


Files format: layerID nodeID nodeID weight
4 layers Multiplex

Nodes: 4458

Edges: 8473997
Genetic
Multiplex
Undirected
Unweighted
ARXIV NETSCIENCE MULTIPLEX

The multiplex consists of layers corresponding to different arXiv categories. To restrict the analysis to a well-defined topic of research, we only included papers with "networks" in the title or abstract up to May 2014.
The multiplex network used in the paper makes use of 13 layers corresponding to:

  1. physics.soc-ph
  2. physics.data-an
  3. physics.bio-ph
  4. math-ph
  5. math.OC
  6. cond-mat.dis-nn
  7. cond-mat.stat-mech
  8. q-bio.MN
  9. q-bio
  10. q-bio.BM
  11. nlin.AO
  12. cs.SI
  13. cs.CV

Ref: Manlio De Domenico, Andrea Lancichinetti, Alex Arenas, and Martin Rosvall - "Identifying Modular Flows on Multilayer Networks Reveals Highly Overlapping Organization in Interconnected Systems" - Physical Review X 5 (2015) 011027


Files format: layerID nodeID nodeID weight
13 layers Multiplex

Nodes: 14489

Edges: 59026
Coauthorship
Multiplex
Undirected
Weighted
PIERRE AUGER MULTIPLEX

The multiplex consists of layers corresponding to different working tasks within the Pierre Auger Collaboration. We considered all submissions between 2010 and 2012 and assigned each report to 16 layers according to its keywords and its content, with manual disambiguation to avoid spurious results from an automated process.
The multiplex network used in the paper makes use of 16 layers corresponding to:

  1. Neutrinos
  2. Detector
  3. Enhancements
  4. Anisotropy
  5. Point-source
  6. Mass-composition
  7. Horizontal
  8. Hybrid-reconstruction
  9. Spectrum
  10. Photons
  11. Atmospheric
  12. SD-reconstruction
  13. Hadronic-interactions
  14. Exotics
  15. Magnetic
  16. Astrophysical-scenarios

Ref: Manlio De Domenico, Andrea Lancichinetti, Alex Arenas, and Martin Rosvall - "Identifying Modular Flows on Multilayer Networks Reveals Highly Overlapping Organization in Interconnected Systems" - Physical Review X 5 (2015) 011027


Files format: layerID nodeID nodeID weight
16 layers Multiplex

Nodes: 514

Edges: 7153
Coauthorship
Multiplex
Undirected
Weighted
FAO MULTIPLEX TRADE NETWORK

We consider different types of trade relationships amoung countries, obtained from FAO (Food and Agriculture Organization of the United Nations). The worldwide food import/export network is an economic network in which layers represent products, nodes are countries and edges at each layer represent import/export relationships of a specific food product among countries. We collected the data from FAO and built the multilayer network corresponding to trading in 2010.
The multiplex network used in the paper is a subset of the full dataset, which consists of 364 layers.

Ref: M. De Domenico, V. Nicosia, A. Arenas, and V. Latora - "Structural reducibility of multilayer networks" - Nature Communications 2015 6, 6864


Files format: layerID nodeID nodeID weight
364 layers Multiplex

Nodes: 214

Edges: 318346
Financial
Multiplex
Directed
Weighted