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Aptaligner specifications

Information


Unique identifier OMICS_13591
Name Aptaligner
Software type Package/Module
Interface Graphical user interface
Restrictions to use None
Input data NGS data, number of projects, project name, library design file
Input format FASTQ, CSV
Output data Alignments performed using a Markov model, alignment scores, calculated statistics
Operating system Unix/Linux
Programming languages C, Python, R
License Other
Computer skills Medium
Stability No
Requirements
xlrd, argeparse, openpyxl, BioPython, R::MiscPsycho, stringr, dendroextras, statmod, numpy, C
Maintained No

Versioning


No version available

Publication for Aptaligner

Aptaligner citation

library_books

Development of Phosphorothioate DNA and DNA Thioaptamers

2017
PMCID: 5618299
PMID: 28703779
DOI: 10.3390/biomedicines5030041

[…] lylamino groups were conjugated to drug hits. Although other high-throughput analysis techniques, such as that reported by Thiel et al. [], work well for random DNA/RNA libraries, Lu et al. developed Aptaligner [] for the automated alignment and decoding of the pseudo-random X-Aptamer sequences. At present, over a dozen modified deoxyuridine reagents are available for use in aptamer synthesis and […]


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Aptaligner institution(s)
UTHealth Bioinformatics Service Center, University of Texas Health Science Center, Houston, TX, USA; Center for Clinical and Translational Sciences, University of Texas Health Science Center, Houston, TX, USA; School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX, USA; Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases, University of Texas Health Science Center, Houston, TX, USA; Department of Nanomedicine and Biomedical Engineering, University of Texas Health Science Center, Houston, TX, USA; School of Medicine, University of Texas Health Science Center, Houston, TX, USA; Department of Integrated Biology and Pharmacology, University of Texas Health Science Center, Houston, TX, USA
Aptaligner funding source(s)
This work was supported by NIH/NCATS (UL1 TR000371), NCI (CA151668), Welch Foundation (AU-1296), NIAID (HHSN272200800048C and AI054827), and NHLBI (HHSN268201000037C) grants.

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