EFI - Enzyme Similarity Tool

This web resource is supported by a Research Resource from the National Institute of General Medical Sciences (R24GM141196-01).
The tools are available without charge or license to both academic and commercial users.

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Submission Name: IP91_RSS_NoFragments Deltaproteobacteria UniRef90_NoFragments_RSS_Deltaproteobacteria

Network Name: IP91_RSS_NoFragments_Deltaproteobacteria_UniRef90_NoFragments_RSS_Deltaproteobacteria_Minlen140_AS11

The parameters used for the initial submission and the finalization are summarized in the table below.

Analysis Summary

Analysis Job Number26656
Network NameIP91_RSS_NoFragments_Deltaproteobacteria_UniRef90_NoFragments_RSS_Deltaproteobacteria_Minlen140_AS11
Alignment Score11
Minimum Length140
Maximum Length50,000
Total Number of Sequences After Filtering26,875

Dataset Summary

EST Job Number26194 (Original Dataset)
Database VersionUniProt: 2022-04 / InterPro: 91
Input OptionAccession IDs (Option D)
Job NameIP91_RSS_NoFragments Deltaproteobacteria UniRef90_NoFragments_RSS_Deltaproteobacteria
Input Sequence SourceUniRef90
E-Value for SSN Edge Calculation5
No matches file
Number of IDs in Uploaded File27,302 (27,302 UniProt ID matches and 0 unmatched)
Taxonomy CategoriesClass: deltaproteobacteria
Family FilterIPR000385, IPR001989, IPR002684, IPR003698, IPR003739, IPR004383, IPR004558, IPR004559, IPR005839, IPR005840, IPR005909, IPR005911, IPR005980, IPR006463, IPR006466, IPR006467, IPR006638, IPR007197, IPR010505, IPR010722, IPR010723, IPR011101, IPR011843, IPR012726, IPR012837, IPR012838, IPR012839, IPR013483, IPR013704, IPR013848, IPR013917, IPR014191, IPR016431, IPR016771, IPR016779, IPR016863, IPR017200, IPR017672, IPR017742, IPR017833, IPR017834, IPR019939, IPR019940, IPR020050, IPR020612, IPR022431, IPR022432, IPR022447, IPR022459, IPR022462, IPR022881, IPR022946, IPR023404, IPR023805, IPR023807, IPR023819, IPR023820, IPR023821, IPR023822, IPR023858, IPR023862, IPR023863, IPR023867, IPR023868, IPR023874, IPR023880, IPR023885, IPR023886, IPR023891, IPR023897, IPR023904, IPR023912, IPR023913, IPR023930, IPR023969, IPR023979, IPR023980, IPR023984, IPR023992, IPR023993, IPR023995, IPR024001, IPR024007, IPR024016, IPR024017, IPR024018, IPR024021, IPR024023, IPR024025, IPR024032, IPR024177, IPR024521, IPR024560, IPR024924, IPR025895, IPR026322, IPR026332, IPR026335, IPR026344, IPR026346, IPR026351, IPR026357, IPR026401, IPR026404, IPR026407, IPR026412, IPR026423, IPR026426, IPR026429, IPR026447, IPR026482, IPR027492, IPR027526, IPR027527, IPR027559, IPR027564, IPR027570, IPR027583, IPR027586, IPR027596, IPR027604, IPR027608, IPR027609, IPR027621, IPR027622, IPR027626, IPR027633, IPR030801, IPR030837, IPR030894, IPR030896, IPR030905, IPR030915, IPR030933, IPR030950, IPR030969, IPR030977, IPR030989, IPR031003, IPR031004, IPR031010, IPR031012, IPR031014, IPR031015, IPR031019, IPR031691, IPR032432, IPR033971, IPR033974, IPR033975, IPR033976, IPR034165, IPR034386, IPR034391, IPR034405, IPR034422, IPR034428, IPR034436, IPR034438, IPR034457, IPR034462, IPR034465, IPR034466, IPR034471, IPR034474, IPR034479, IPR034480, IPR034485, IPR034491, IPR034497, IPR034498, IPR034505, IPR034508, IPR034514, IPR034515, IPR034519, IPR034529, IPR034530, IPR034531, IPR034532, IPR034534, IPR034547, IPR034556, IPR034557, IPR034559, IPR034560, IPR034687, IPR038135, IPR039661, IPR040063, IPR040072, IPR040074, IPR040081, IPR040082, IPR040085, IPR040086, IPR040087, IPR040088, IPR041582, IPR045375, IPR045567, IPR045784, PF04055, PF06969, PF08497, PF12345, PF13186, PF16199, PF16881, PF19238, PF19288, PF19864
Exclude FragmentsYes
Total Number of Sequences in Dataset27,081
Total Number of Edges19,480,654
Number of Unique Sequences27,081
Convergence Ratio?0.053
Please cite your use of the EFI tools:

Rémi Zallot, Nils Oberg, and John A. Gerlt, The EFI Web Resource for Genomic Enzymology Tools: Leveraging Protein, Genome, and Metagenome Databases to Discover Novel Enzymes and Metabolic Pathways. Biochemistry 2019 58 (41), 4169-4182. https://doi.org/10.1021/acs.biochem.9b00735

Nils Oberg, Rémi Zallot, and John A. Gerlt, EFI-EST, EFI-GNT, and EFI-CGFP: Enzyme Function Initiative (EFI) Web Resource for Genomic Enzymology Tools. J Mol Biol 2023. https://doi.org/10.1016/j.jmb.2023.168018

The panels below provide files for full and representative node SSNs for download with the indicated numbers of nodes and edges. As an approximate guide, SSNs with ~2M edges can be opened with 16 GB RAM, ~5M edges can be opened with 32 GB RAM, ~10M edges can be opened with 64 GB RAM, ~20M edges can be opened with 128 GB RAM, ~40M edges can be opened with 256 GB RAM, and ~120M edges can be opened with 768 GB RAM.

Files may be transferred to the Genome Neighborhood Tool (GNT), the Color SSN utility, the Cluster Analysis utility, or the Neighborhood Connectivity utility.

Full Network ?

Each node in the network represents a single protein sequence.

# Nodes # Edges
26,875 15,107,300

 

Representative Node Networks ?

In representative node (RepNode) networks, each node in the network represents a collection of proteins grouped according to percent identity. For example, for a 75% identity RepNode network, all connected sequences that share 75% or more identity are grouped into a single node (meta node). Sequences are collapsed together to reduce the overall number of nodes, making for less complicated networks easier to load in Cytoscape.

The cluster organization is not changed, and the clustering of sequences remains identical to the full network.

% ID # Nodes # Edges
100 26,875 15,107,300
95 26,862 15,086,126
90 26,828 15,045,659
85 25,913 14,017,553
80 24,950 12,966,003
75 23,958 11,882,662
70 22,919 10,831,392
65 21,774 9,832,621
60 20,507 8,807,678
55 19,055 7,673,863
50 17,385 6,484,377
45 15,604 5,404,643
40 13,683 4,379,150

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Portions of these data are derived from the Universal Protein Resource (UniProt) databases.

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