Supplementary data: Understanding cancer complexome using networks, spectral graph theory and multilayer framework
Creators: name: Rai, Aparna
name: Jalan, Sarika
Publisher: name: figshare
Year: 2017
Subjects: subject: Cancer
subject: Biophysics
subject: 60109 Proteomics and Intermolecular Interactions (excl. Medical Proteomics)
subject: FOS: Biological sciences
subject: FOS: Biological sciences
subject: 60114 Systems Biology

description: We consider seven cancer tissues for our analysis namely, · Breast · Oral · Ovarian · Cervical · Lung · Colon · Prostate There are two basic components of a network namely, nodes and edges. Here we study protein-protein interaction (PPI) networks of the normal and the disease cells where nodes are the proteins and edges denote interactions between the proteins. The nodes in the normal and the disease network are selected on the basis of their expression in a cell existing in the normal or disease tissue, respectively. The interactions between a pair of proteins is considered if there exists a direct (i.e. physical), indirect (i.e. functional) or both relation between them. So in total, there are fourteen networks for these seven diseases, one is the normal network and other is the cancer/disease network. <b>DATA INFORMATION</b> 1. The data for each network consist of two columns, and is in the form of an Adjacency list, which depicts the PPIs. Both the columns show how a protein is interacting with other protein. 2. There are fourteen files, where each cancer constitutes to have two files, one for normal state and other for the disease state. 3. Sample of the network: Protein1 Protein 2 Protein 4 Protein 7 Protein 2 Protein 8 |<br> | | | Protein N Protein N-4 Where, N is the number of proteins in each of the network. 4. Note that the networks, which we provide here, are the complete networks. They are disconnected networks. Apart from these fourteen networks, we have their connected components. Since, these fourteen networks are disconnected, for some analysis such as diameter, spectra, we have to consider the largest connected component/s (LCC) of these networks, which can easily be done from any algorithm. We provide the details of all the connected components for each of these fourteen networks. · Please note that, the networks corresponding to Breast, Oral, Ovarian, Colon and Prostate consist of only one big connected component that is, for these five diseases there are ten connected components one for each normal and disease. · Further, for Cervical and Lung, there are more than one big connected component. · The statistics of whole networks and connected components for each network is tabulated below. Network Whole network Number of Nodes Connected Components Breast Normal 1 2464 1 Disease 1 2096 1 Oral Normal 1 2105 1 Disease 1 1542 1 Ovarian Normal 1 1869 1 Disease 1 2085 1 Cervical Normal 1 3559 5 Disease 1 2397 3 Lung Normal 1 3861 3 Disease 1 3131 3 Colon Normal 1 4932 1 Disease 1 3458 1 Prostate Normal 1 2357 1 Disease 1 5180 1 Total -------- 14 ------ 24 We have provided data for fourteen whole networks as protein-protein interactions. The connected components of these 14 datasets can easily be found through various algorithms and alogo based softwares (e.g. cytoscape). However, on request, the data for the 24 connected components can also be provided. 5. Further, we also provide files which shows the list of proteins involved in particular normal of disease dataset. We name it as protein index. These files contain the number of proteins (N) in each dataset and are names as Protein_index. 6. We also provide the list of complete duplicated nodes for all the normal and disease datasets. For further information on how we collect the data can be found in the manuscript and supplementary file.