eBLOCKs specifications


Unique identifier OMICS_21024
Name eBLOCKs
Restrictions to use None
Community driven No
Data access File download, Browse
User data submission Not allowed
Maintained No


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Publication for eBLOCKs

eBLOCKs citations


Classification of protein sequences by means of irredundant patterns

BMC Bioinformatics
PMCID: 3009487
PMID: 20122187
DOI: 10.1186/1471-2105-11-S1-S16

[…] ng sequence similarity; conversely the eMOTIF database method [] defines the kernel in terms of the sequence motifs that appear in a pair of sequences. These motifs were previously extracted from the eBLOCKs database using the eMOTIF-maker algorithm that derives patterns from sequence alignments [,].More recently, the Local Alignment method [] mimics the behavior of the Smith-Waterman score to bui […]


A discriminative method for protein remote homology detection and fold recognition combining Top n grams and latent semantic analysis

BMC Bioinformatics
PMCID: 2613933
PMID: 19046430
DOI: 10.1186/1471-2105-9-510

[…] en k-mers and introduce a feature vector based on the distances between the k-mers. The feature vector of eMOTIF kernel [] is based on motifs extracted with the unsupervised eMOTIF method [] from the eBLOCKS database []. GPkernel [] is another motif kernel based on discrete sequence motifs, which are evolved using genetic programming. SVM-HUSTLE [] builds a SVM classifier for a query sequence by t […]

eBLOCKs institution(s)
Abgenix, Inc., Fremont, CA, USA; Oracle Corporation, , Redwood shores, CA, USA; Department of Biochemistry, Stanford University, Stanford, CA, USA; Biomedical Informatics, Stanford University, Stanford, CA, USA
eBLOCKs funding source(s)
Supported by a grant from NHGRI HG02235-07.

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