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Fig. 1 | BMC Bioinformatics

Fig. 1

From: \({\text{COSNet}}_i\): ComplexOme-Structural Network Interpreter used to study spatial enrichment in metazoan ribosomes

Fig. 1

COSNet\(_i\) step-by-step detailed workflow. Also related to Additional file 1 where the two detailed examples from this manuscript were optimized and developed. \({\text{COSNet}}_i\) is divided in five steps that must be completed plus accessory functions that allow users to perform quality control checks or produce alternative outputs along the way. The input data is an mmCIF file. Step 1 extracts all the protein entities from the input file as PDBs using split_cif_by_entity.py. Additionally, Step 1’ allows checking the percentage of coverage of each modelled protein sequence as compared to its FASTA sequence using check_cif_completeness.py. Step 2 prepares the PDB files by building a list of combined names for each protein pair using combination.py. In parallel the workflow offers as Step 2’ the opportunity to reindex the residues column inside PDBs in case there are disruptions in the structures that would lead to holes by using reindex_pdb.py or its batch counterpart batch_reindex_pdb.py. Step 3 takes the list of PDB combinations and fits distance matrices across each file pair using calculate_distance.py or its batch counterpart batch_calc_dist.py. Step 4 uses the distance matrices to build a list of contacts and a graph through the use of contacts_from_dist.py. Finally, Step 5.1 integrates the Omics abundances into the graph analyses through intcryomics.py. Alternatively, if there is not a binary Omics file users may rely on Step 5.2 intcryomics_sigassign.py to manually select the protein entities that feature significant changes. Step 5.1’ returns customized graph files that can be used to highlight specific regions in the networks using pimp_my_network.py while Step 5.2’ allows users to investigate structural coherence in the regions selected through the existing graph community detection algorithm Infomap using Region_selection_infomap.py. mmCIF icon was taken from IUCr

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