Clust statistics

info info

Citations per year


Popular tool citations

chevron_left Gene co-expression prediction Gene expression clustering chevron_right

Tool usage distribution map

Tool usage distribution map
info info

Associated diseases

Associated diseases
Want to access the full stats & trends on this tool?


Clust specifications


Unique identifier OMICS_24103
Name Clust
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python
Computer skills Advanced
Version 1.4.0
Stability Stable
numpy, scipy, matplotlib, sklearn, sompy, joblib, portalocker
Maintained Yes




No version available



  • person_outline Steven Kelly

Publication for Clust

Clust citations


Effective Network Size Predicted From Simulations of Pathogen Outbreaks Through Social Networks Provides a Novel Measure of Structure Standardized Group Size

PMCID: 5943561
PMID: 29774217
DOI: 10.3389/fvets.2018.00071

[…] become infected; for γ, the 0.10 indicated that per daily timestep, each infected individual had a 10% probability of recovering. these methods are available through r package enss as functions “clust_sim_si” and “clust_sim_sir,” respectively. although we chose to focus our efforts by using unweighted networks and testing only one value for β, we also present analyses that investigate […]


Improving the understanding of sleep apnea characterization using Recurrence Quantification Analysis by defining overall acceptable values for the dimensionality of the system, the delay, and the distance threshold

PLoS One
PMCID: 5886413
PMID: 29621264
DOI: 10.1371/journal.pone.0194462

[…] matrix a used in their definitions is the recurrence matrix from which the identity matrix is subtracted (aij = rij−δij where δij is the kronecker delta) []., the clustering coefficient [] is: clust=∑i=1n∑j,k=1nai,jaj,kak,irri(13) where rri=∑j=1nai,j is the local recurrence rate., the transitivity [] is: trans=∑i,j,k=1najkaijaik∑i,j,k=1naijaik(14), the crp toolbox (provided by tocsy: […]


Sensorimotor Representation of Speech Perception. Cross Decoding of Place of Articulation Features during Selective Attention to Syllables in 7T fMRI

PMCID: 5880028
PMID: 29610768
DOI: 10.1523/ENEURO.0252-17.2018

[…] across variation of three manner of articulation features (i.e., stop, fricative, and nasal)., generalization maps after correction for multiple comparisons using cluster-size thresholding (p-clust < 0.05) during the performance of the attend to vowels task are presented in . the generalization maps revealed successful decoding of place of articulation within regions of the brain’s […]


Cell Based Reporter System for High Throughput Screening of MicroRNA Pathway Inhibitors and Its Limitations

Front Genet
PMCID: 5835079
PMID: 29535760
DOI: 10.3389/fgene.2018.00045

[…] both potential inhibitors and activators of rna silencing, were selected and tested in the validation dose-response experiments. data were hierarchically clustered using the python library inchlib_clust and visualized with the corresponding javascript library inchlib (skuta et al., ). the clustering was performed with a combination of the ward's linkage algorithm (ward, ) and the classic […]


Diversification of Secondary Metabolite Biosynthetic Gene Clusters Coincides with Lineage Divergence in Streptomyces

PMCID: 5872123
PMID: 29438308
DOI: 10.3390/antibiotics7010012

[…] columns report the affiliated genome, clade, gene cluster class (hybrids are indicated by hyphens), gene cluster length (bp), natural product annotation provided by antismash, cluster membership (clust memb), mibig database identification, the portion of genes with similarity to genes within the most similar known cluster from the mibig database (% genes w/similarity). cluster membership […]


Motor Unit Action Potential Clustering—Theoretical Consideration for Muscle Activation during a Motor Task

Front Hum Neurosci
PMCID: 5797735
PMID: 29445332
DOI: 10.3389/fnhum.2018.00015

[…] pattern. to this end, we modeled two emg signals, whereby a single muap was either convolved with a randomly distributed impulse train (emg-rand) or a “clustered” sequence of impulses (emg-clust). the clustering occurred in windows lasting 5–100 ms. a final mixed signal of emg-clust and emg-rand, with ratios (1:1–1:10), was also modeled. a ratio of 1:1 would indicate that 50% of muap […]

Want to access the full list of citations?
Clust institution(s)
Department of Plant Sciences, University of Oxford, South Parks Road, Oxford, UK

Clust reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review Clust