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.

Download Network Files

Submission Name: IP91_IPR004184_NoFragments Eukaryota UniRef90_NoFragments_IPR004184_Fungi

Network Name: IP91_IPR004184_NoFragments_Eukaryota_UniRef90_NoFragments_IPR004184_Fungi_Minlen650_AS240

SSN Overview
Network Files

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

Analysis Summary

Analysis Job Number	26609
Network Name	IP91_IPR004184_NoFragments_Eukaryota_UniRef90_NoFragments_IPR004184_Fungi_Minlen650_AS240
Alignment Score	240
Minimum Length	650
Maximum Length	50,000
Total Number of Sequences After Filtering	28

Dataset Summary

EST Job Number	26151 (Original Dataset)
Database Version	UniProt: 2022-04 / InterPro: 91
Input Option	Accession IDs (Option D)
Job Name	IP91_IPR004184_NoFragments Eukaryota UniRef90_NoFragments_IPR004184_Fungi
Input Sequence Source	UniRef90
E-Value for SSN Edge Calculation	5
No matches file
Number of IDs in Uploaded File	110 (110 UniProt ID matches and 0 unmatched)
Taxonomy Categories	Fungi
Family Filter	IPR004184
Exclude Fragments	Yes
Total Number of Sequences in Dataset	37
Total Number of Edges	343
Number of Unique Sequences	37
Convergence Ratio?	0.515

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
	28	161

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	28	161
95	28	161
90	27	150
85	26	136
80	26	136
75	26	136
70	25	127
65	24	114
60	24	114
55	24	114
50	24	114
45	24	114
40	24	114

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

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% ID	# Nodes	# Edges
100	28	161
95	28	161
90	27	150
85	26	136
80	26	136
75	26	136
70	25	127
65	24	114
60	24	114
55	24	114
50	24	114
45	24	114
40	24	114

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% ID	# Nodes	# Edges
100	28	161
95	28	161
90	27	150
85	26	136
80	26	136
75	26	136
70	25	127
65	24	114
60	24	114
55	24	114
50	24	114
45	24	114
40	24	114

% ID	# Nodes	# Edges
100	28	161
95	28	161
90	27	150
85	26	136
80	26	136
75	26	136
70	25	127
65	24	114
60	24	114
55	24	114
50	24	114
45	24	114
40	24	114