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RESQUE specifications


Unique identifier OMICS_20197
Alternative name REduction-based scheme using Semi-Markov scores for network QUErying
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Version 1.00
Stability Stable
Source code URL
Maintained Yes


No version available


  • person_outline Byung-Jun Yoon

Publication for REduction-based scheme using Semi-Markov scores for network QUErying

RESQUE citations


CBS mutations are good predictors for B6‐responsiveness: A study based on the analysis of 35 Brazilian Classical Homocystinuria patients

PMCID: 5902399
PMID: 29352562
DOI: 10.1002/mgg3.342

[…] r genetic heterogeneity of Brazil as compared with other Latin American countries and, possibly, the more limited contribution of Spanish immigration to Brazil (IBGE, ; Kehdy et al., ; Pena et al., ; Resque et al., ). Wide phenotypic variability has been observed for this mutation, with mild to severe phenotypes and pyridoxine responsiveness ranging from partial to absent (Kraus, ; Urreizti et al. […]


CUFID query: accurate network querying through random walk based network flow estimation

BMC Bioinformatics
PMCID: 5751815
PMID: 29297279
DOI: 10.1186/s12859-017-1899-y
call_split See protocol

[…] in order to estimate node correspondence scores. It performs a random walk over the Kronecker product between two networks, and utilizes the score to derive a global network alignment. SMETANA [] and RESQUE [] adopt a semi-Markov random walk (SMRW) model []. In the SMRW model, the staying time of the random walker at the pair of nodes is proportional to the topological similarity and the pairwise […]


MediSyn: uncertainty aware visualization of multiple biomedical datasets to support drug treatment selection

BMC Bioinformatics
PMCID: 5606218
PMID: 28929971
DOI: 10.1186/s12859-017-1785-7

[…] for each system. During the actual tasks, participants were allowed to use pen and paper.The participants then completed a questionnaire for each system in T1. The questionnaire adopted the design of ResQue [] and Knijnenburg et al. []. For T2, participants were encouraged to think aloud while exploring the datasets. Afterward, the participants completed another questionnaire on the trustworthines […]


Ancestry informative markers and selected single nucleotide polymorphisms in immunoregulatory genes on preterm labor and preterm premature rupture of membranes: a case control study

PMCID: 4743423
PMID: 26846412
DOI: 10.1186/s12884-016-0823-1

[…] For the identification of maternal Ancestry Informative Markers, a panel of 61 selected insertion/deletion (indel) variable sites were amplified in conditions as described by Resque et al. []. The indel markers that constitute this panel were selected based on the characteristic of exhibiting substantially different frequencies between population from different geographic […]


Reduced cortical expression of a newly identified splicing variant of the DLG1 gene in patients with early onset schizophrenia

PMCID: 4930131
PMID: 26440542
DOI: 10.1038/tp.2015.154

[…] An in silico structural analysis of exon 3b of the human DLG1 gene using ESEfinder, FAS-ESS, and RESQUE-ESS indicated the presence of an exonic splicing enhancer (ESE) consensus (TGAAAGAAT) in exon 3b (). This consensus sequence includes the SNP rs3915512 (underlined portion: TGA(A/T)AGAAT), the […]


Accurate multiple network alignment through context sensitive random walk

BMC Syst Biol
PMCID: 4331682
PMID: 25707987
DOI: 10.1186/1752-0509-9-S1-S7

[…] lignment of multiple biological sequences, making it one of the most popular approaches for sequence alignment. Recently, the MEA approach has been also applied to comparative network analysis, where RESQUE [] performs MEA-based network querying and SMETANA [] performs MEA-based multiple network alignment. […]


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RESQUE institution(s)
Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
RESQUE funding source(s)
Supported in part by the National Science Foundation, through NSF Award CCF-1149544.

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