An efficient algorithm for large-scale detection of protein families.

By Anton J. Enright, Stijn van Dongen, Christos A. Ouzounis. Nucleic Acids Research, 2002

3,667 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d45f2b8f6819fc4c524794b3cfc0fa4c4f7d43f4

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Citations in the corpus

Reprogramming of miRNA networks in cancer and leukemia. (2010, methodology): “, groups of densely connected nodes) from biological nets and we chose the MCL graph-based algorithm (Enright et al. 2002).”
PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors (2013, methodology): “Then we classi-ﬁed these proteins into clusters by TribeMCL (29).”
A travel guide to Cytoscape plugins (2012, methodology): “MCL-new and APCluster implement the popular network clustering algorithms developed by Van Dongen 27 and Frey et al. 28 , respectively, for clustering in general.”
Evaluation of clustering algorithms for protein-protein interaction networks (2006, methodology): “The four methods tested here are Markov Clustering (MCL [35,36]), Restricted Neighborhood Search Clustering (RNSC [21]), Molecular Complex Detection (MCODE [19]), and Super Paramagnetic Clustering (SPC [37]).”
Estimating gene gain and loss rates in the presence of error in genome assembly and annotation using CAFE 3. (2013, methodology): “For each pair of genome annotations (i.e., for each species), we assigned genes to gene families using an all-against-all BLASTP sequence similarity search, followed by clustering using the MCL algorithm (Enright et al. 2002).”
OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species (2015, background): “This allows users to submit their own orthologous cluster files generated by other software such as OrthoMCL.”
iFC2: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content (2010, methodology): “Numerous computational methods have been proposed for sequence-based prediction of the family and superfamily (Enright et al. 2002; Melvin et al. 2007; Gewehr et al. 2007), the fold type (Ding and Dubchak 2001; Hvidsten et al.”
Large-Scale Determination of Sequence, Structure, and Function Relationships in Cytosolic Glutathione Transferases across the Biosphere (2014, methodology): “To help guide the choice of threshold for these full networks, we applied the Markov Cluster Algorithm (MCL) [35], an objective method that has been used to detect protein families [36], to the representative network data.”
Ensembl comparative genomics resources (2016, methodology): “BLAST scores are fed into MCL to group the sequences by their similarity.”
ACLAME: A CLAssification of Mobile genetic Elements, update 2010 (2009, background): “The second step, unchanged, runs the clustering algorithm MCL (12) (inflation factor 1.2) with the list of paired sequences (each sequence defining a node in the graph) and using the E-values for defining the graph weighted edges.”
Large-scale prediction of long non-coding RNA functions in a coding–non-coding gene co-expression network (2011, background): “Genes within a co-expressed module commonly have similar functions, thus, mining modules in a network is an efficient approach for predicting gene functions (42,43).”