Aptamer base: a collaborative knowledge base to describe aptamers and SELEX experiments
Open accessAbstract
Over the past several decades, rapid developments in both molecular and information technology have collectively increased our ability to understand molecular recognition. One emerging area of interest in molecular recognition research includes the isolation of aptamers. Aptamers are single-stranded nucleic acid or amino acid polymers that recognize and bind to targets with high affinity and selectivity. While research has focused on collecting aptamers and their interactions, most of the information regarding experimental methods remains in the unstructured and textual format of peer reviewed publications. To address this, we present the Aptamer Base, a database that provides detailed, structured information about the experimental conditions under which aptamers were selected and their binding affinity quantified. The open collaborative nature of the Aptamer Base provides the community with a unique resource that can be updated and curated in a decentralized manner, thereby accommodating the ever evolving field of aptamer research. DATABASE URL: http://aptamer.freebase.com.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
High-affinity aptamers recognize more than 900 different targets.
“At present, high-affinity aptamers recognize more than 900 different targets, including cytokines, growth factors, proteases, immunoglobulins, cell surface receptors, and cell adhesion molecules.240,241”
From Smart nanoparticles for cancer therapy (2023) · cites this paper as [240]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
1 retracted
Reprogramming bacteria to seek and destroy an herbicide
Sinha, J., Reyes, S. J., & Gallivan, J. P. (2010) · Nature Chemical Biology · doi:10.1038/nchembio.369 · Cited by 166 · see citing works
RetractedTuerk, C., & Gold, L. (1990) · Science · doi:10.1126/science.2200121 · Cited by 10,421 · see citing works
In vitro selection of RNA molecules that bind specific ligands
Ellington, A. D., & Szostak, J. W. (1990) · Nature · doi:10.1038/346818a0 · Cited by 9,845 · see citing works
The Entity Relationship Model — Toward a Unified View of Data
Chen, P. P.-S. (2002) · Springer eBooks · doi:10.1007/978-3-642-59412-0_18 · Cited by 5,751 · see citing works
The entity-relationship model—toward a unified view of data
Chen, P. P.-S. (1976) · ACM Transactions on Database Systems · doi:10.1145/320434.320440 · Cited by 4,708 · see citing works
Mathews, D. H., Sabina, J., Zuker, M., & Turner, D. H. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.2700 · Cited by 3,795 · see citing works
Aptamers: An Emerging Class of Molecules That Rival Antibodies in Diagnostics
Jayasena, S. D. (1999) · Clinical Chemistry · doi:10.1093/clinchem/45.9.1628 · Cited by 2,146 · see citing works
Mathews, D. H., Disney, M. D., Childs‐Disney, J. L., Schroeder, S. J., Zuker, M., & Turner, D. H. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0401799101 · Cited by 1,609 · see citing works
The minimum information about a genome sequence (MIGS) specification
Field, D., Garrity, G. M., Gray, T., Morrison, N., Selengut, J., Sterk, P., Tatusova, T. A., Thomson, N. R., Allen, M. J., Angiuoli, S. V., et al. (2008) · Nature Biotechnology · doi:10.1038/nbt1360 · Cited by 1,148 · see citing works
Aptamers: An Emerging Class of Therapeutics
Nimjee, S. M., Rusconi, C. P., & Sullenger, B. A. (2005) · Annual Review of Medicine · doi:10.1146/annurev.med.56.062904.144915 · Cited by 940 · see citing works
The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data
Parisien, M., & Major, F. (2008) · Nature · doi:10.1038/nature06684 · Cited by 830 · see citing works
Applications of Aptamers as Sensors
Cho, E. J., Lee, J.-W., & Ellington, A. D. (2009) · Annual Review of Analytical Chemistry · doi:10.1146/annurev.anchem.1.031207.112851 · Cited by 792 · see citing works
Benson, D. A., Karsch‐Mizrachi, I., Lipman, D. J., Ostell, J., & Sayers, E. W. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1079 · Cited by 552 · see citing works
Beyond natural antibodies: the power of in vitro display technologies
Bradbury, A. M., Sidhu, S. S., Dübel, S., & McCafferty, J. (2011) · Nature Biotechnology · doi:10.1038/nbt.1791 · Cited by 548 · see citing works
Aptamers as therapeutic and diagnostic agents
Brody, E. N., & Gold, L. (2000) · Reviews in Molecular Biotechnology · doi:10.1016/s1389-0352(99)00004-5 · Cited by 495 · see citing works
Chemical Entities of Biological Interest: an update
de Matos, P., Alcántara, R., Dekker, A., Ennis, M., Hastings, J., Haug, K., Spiteri, I., Turner, S., & Steinbeck, C. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp886 · Cited by 319 · see citing works
Developing aptamers into therapeutics
White, R. R., Sullenger, B. A., & Rusconi, C. P. (2000) · Journal of Clinical Investigation · doi:10.1172/jci11325 · Cited by 297 · see citing works
Memory efficient folding algorithms for circular RNA secondary structures
Hofacker, I. L., & Stadler, P. F. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl023 · Cited by 202 · see citing works
Phage Display: Selecting Straws Instead of a Needle from a Haystack
Vodnik, M., Žager, U., Štrukelj, B., & Lunder, M. (2011) · Molecules · doi:10.3390/molecules16010790 · Cited by 199 · see citing works
Lee, J. F. (2004) · Nucleic Acids Research · doi:10.1093/nar/gkh094 · Cited by 188 · see citing works
Screening and Initial Binding Assessment of Fumonisin B1 Aptamers
McKeague, M., Bradley, C. R., Girolamo, A. D., Visconti, A., Miller, J. D., & DeRosa, M. C. (2010) · International Journal of Molecular Sciences · doi:10.3390/ijms11124864 · Cited by 153 · see citing works
Self-citationThe next-generation sequencing technology and application
Zhou, X., Ren, L., Meng, Q., Li, Y., Yu, Y., & Yu, J. M. (2010) · Protein & Cell · doi:10.1007/s13238-010-0065-3 · Cited by 151 · see citing works
Computational approaches to RNA structure prediction, analysis, and design
Laing, C., & Tamar Schlick, A. (2011) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2011.03.015 · Cited by 149 · see citing works
(2003) · Methods and principles in medicinal chemistry · doi:10.1002/3527601813 · Cited by 132 · see citing works
In Vitro Selection of DNA Aptamers to Glioblastoma Multiforme
Bayraç, A. T., Sefah, K., Parekh, P. A., Bayraç, C., Gülbakan, B., Öktem, H. A., & Tan, W. (2011) · ACS Chemical Neuroscience · doi:10.1021/cn100114k · Cited by 117 · see citing works
Petabyte-scale innovations at the European Nucleotide Archive
Cochrane, G., Akhtar, R., Bonfield, J., Bower, L., Demiralp, F., Faruque, N., Gibson, R., Hoad, G., Hubbard, T., Hunter, C., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn765 · Cited by 105 · see citing works
DDBJ launches a new archive database with analytical tools for next-generation sequence data
Kaminuma, E., Mashima, J., Kodama, Y., Gojobori, T., Ogasawara, O., Okubo, K., Takagi, T., & Nakamura, Y. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp847 · Cited by 99 · see citing works
Stead, S. L., Ashwin, H. M., Johnston, B. H., Dallas, A., Kazakov, S. A., Tarbin, J. A., Sharman, M., Kay, J. F., & Keely, B. J. (2010) · Analytical Chemistry · doi:10.1021/ac902226v · Cited by 98 · see citing works
Ramalingam, D., Duclair, S., Datta, S. A. K., Ellington, A. D., Rein, A. R., & Prasad, V. R. (2010) · Journal of Virology · doi:10.1128/jvi.02626-09 · Cited by 89 · see citing works
Functional Nucleic Acids for Analytical Applications
Li, Y., & Yi, L. (2009) · Springer eBooks · doi:10.1007/978-0-387-73711-9 · Cited by 71 · see citing works
Silverman, S. K. (2009) · Springer eBooks · doi:10.1007/978-0-387-73711-9_3 · Cited by 52 · see citing works
Kim, Y., Sung, H. J., Kim, S., Kim, E.-O., Lee, J. W., Moon, J.-Y., Choi, K., Jung, J.-E., Lee, Y., Koh, S. S., et al. (2011) · Cancer Letters · doi:10.1016/j.canlet.2011.08.027 · Cited by 42 · see citing works
Advances in Methods for Therapeutic Peptide Discovery, Design and Development
Pirogova, E., Istivan, T. S., Gan, E., & Ćosić, I. (2011) · Current Pharmaceutical Biotechnology · doi:10.2174/138920111796117436 · Cited by 41 · see citing works
RiboaptDB: A Comprehensive Database of Ribozymes and Aptamers
Thodima, V. J., Pirooznia, M., & Deng, Y. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-s2-s6 · Cited by 36 · see citing works
Advances in Aptamer-Based Biosensors for Food Safety
McKeague, M., Giamberardino, A., & Maria, C. (2011) · InTech eBooks · doi:10.5772/22350 · Cited by 31 · see citing works
Self-citationPonomarenko, J. V. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.195 · Cited by 28 · see citing works
Theoretical Principles of In Vitro Selection Using Combinatorial Nucleic Acid Libraries
Vant-Hull, B., Gold, L., & Zichi, D. A. (2000) · Current Protocols in Nucleic Acid Chemistry · doi:10.1002/0471142700.nc0901s00 · Cited by 25 · see citing works
SciDBMaker: new software for computer-aided design of specialized biological databases
Hammami, R., Zouhir, A., Naghmouchi, K., Hamida, J. B., & Fliss, I. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-121 · Cited by 20 · see citing works
Don't forget people and specimens that make the database
Campbell, D. G. (2008) · Nature · doi:10.1038/455590b · Cited by 5 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Smart nanoparticles for cancer therapy
Sun, L., Liu, H., Ye, Y., Lei, Y., Islam, R., Tan, S., Tong, R., Miao, Y.-B., & Cai, L. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01642-x · Cited by 1,073 · see citing works
Current approaches in SELEX: An update to aptamer selection technology
Darmostuk, M., Rimpelová, S., Gbelcová, H., & Ruml, T. (2015) · Biotechnology Advances · doi:10.1016/j.biotechadv.2015.02.008 · Cited by 703 · see citing works
Luka, G., Ahmadi, A., Najjaran, H., Alocilja, E. C., DeRosa, M. C., Wolthers, K. R., Malki, A. M., Aziz, H. A., Thani, A. A. A., & Hoorfar, M. (2015) · Sensors · doi:10.3390/s151229783 · Cited by 570 · see citing works
Self-citationChallenges and Opportunities for Small Molecule Aptamer Development
McKeague, M., & DeRosa, M. C. (2012) · Journal of Nucleic Acids · doi:10.1155/2012/748913 · Cited by 468 · see citing works
Self-citationAutomated physics-based design of synthetic riboswitches from diverse RNA aptamers
Borujeni, A. E., Mishler, D. M., Wang, J., Huso, W. D., & Salis, H. M. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1289 · Cited by 265 · see citing works
Aptamer Nanomedicine for Cancer Therapeutics: Barriers and Potential for Translation
Lao, Y., Phua, K. K. L., & Leong, K. W. (2015) · ACS Nano · doi:10.1021/nn507494p · Cited by 257 · see citing works
Capture-SELEX for aptamer selection: A short review
Lyu, C., Khan, I. M., & Wang, Z. (2021) · Talanta · doi:10.1016/j.talanta.2021.122274 · Cited by 254 · see citing works
Dynamic DNA nanotechnology: toward functional nanoscale devices
DeLuca, M., Shi, Z., Castro, C. E., & Arya, G. (2019) · Nanoscale Horizons · doi:10.1039/c9nh00529c · Cited by 211 · see citing works
In vitro selection of aptamers and their applications
DeRosa, M. C., Lin, A. K., Mallikaratchy, P. R., McConnell, E. M., McKeague, M., Patel, R., & Shigdar, S. L. (2023) · Nature Reviews Methods Primers · doi:10.1038/s43586-023-00238-7 · Cited by 191 · see citing works
Self-citationAnalysis of In Vitro Aptamer Selection Parameters
McKeague, M., McConnell, E. M., Cruz-Toledo, J., Bernard, E. D., Pach, A., Mastronardi, E., Zhang, X., Beking, M., Francis, T., Giamberardino, A., et al. (2015) · Journal of Molecular Evolution · doi:10.1007/s00239-015-9708-6 · Cited by 170 · see citing works
Self-citationAptamers: The “evolution” of SELEX
Wu, Y. X., & Kwon, Y. J. (2016) · Methods · doi:10.1016/j.ymeth.2016.04.020 · Cited by 165 · see citing works
Kinghorn, A. B., Fraser, L. A., Liang, S., Shiu, S. C., & Tanner, J. A. (2017) · International Journal of Molecular Sciences · doi:10.3390/ijms18122516 · Cited by 164 · see citing works
Artificial Intelligence in Aptamer–Target Binding Prediction
Chen, Z., Hu, L., Zhang, B., Lü, A., Wang, Y., Yu, Y., & Zhang, G. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22073605 · Cited by 150 · see citing works
McKeague, M., Velu, R., Hill, K., Bardóczy, V., Mészáros, T., & DeRosa, M. C. (2014) · Toxins · doi:10.3390/toxins6082435 · Cited by 149 · see citing works
Self-citationSelection of Nucleic Acid Aptamers Targeting Tumor Cell-Surface Protein Biomarkers
Mercier, M.-C., Dontenwill, M., & Choulier, L. (2017) · Cancers · doi:10.3390/cancers9060069 · Cited by 113 · see citing works
Ultrasensitive Norovirus Detection Using DNA Aptasensor Technology
Giamberardino, A., Labib, M., Hassan, E. M., Tetro, J. A., Springthorpe, S., Sattar, S. A., Berezovski, M. V., & DeRosa, M. C. (2013) · PLoS ONE · doi:10.1371/journal.pone.0079087 · Cited by 110 · see citing works
Self-citationHigh resolution grating-assisted surface plasmon resonance fiber optic aptasensor
Albert, J., Lépinay, S., Caucheteur, C., & DeRosa, M. C. (2013) · Methods · doi:10.1016/j.ymeth.2013.07.007 · Cited by 95 · see citing works
Self-citationRöthlisberger, P., Gasse, C., & Hollenstein, M. (2017) · International Journal of Molecular Sciences · doi:10.3390/ijms18112430 · Cited by 93 · see citing works
Opportunities in the design and application of RNA for gene expression control
McKeague, M., Wong, R. S., & Smolke, C. D. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw151 · Cited by 76 · see citing works
Self-citationComputational tools for aptamer identification and optimization
Sun, D., Sun, M., Zhang, J., Lin, X., Zhang, Y., Lin, F., Zhang, P., Yang, C. J., & Song, J. T. (2022) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2022.116767 · Cited by 73 · see citing works
Catalytic RNA, ribozyme, and its applications in synthetic biology
Park, S. V., Yang, J., Jo, H., Kang, B., Oh, S. S., & Jung, G. Y. (2019) · Biotechnology Advances · doi:10.1016/j.biotechadv.2019.107452 · Cited by 70 · see citing works
Enhancing aptamer function and stability via in vitro selection using modified nucleic acids
Meek, K. N., Rangel, A. E., & Heemstra, J. M. (2016) · Methods · doi:10.1016/j.ymeth.2016.03.008 · Cited by 69 · see citing works
AptaNet as a deep learning approach for aptamer–protein interaction prediction
Emami, N., & Ferdousi, R. (2021) · Scientific Reports · doi:10.1038/s41598-021-85629-0 · Cited by 68 · see citing works
Hasanzadeh, A., Hamblin, M. R., Kiani, J., Noori, H., Hardie, J. M., Karimi, M., & Shafiee, H. (2022) · Nano Today · doi:10.1016/j.nantod.2022.101665 · Cited by 69 · see citing works
McConnell, E. M., Holahan, M. R., & DeRosa, M. C. (2014) · Nucleic Acid Therapeutics · doi:10.1089/nat.2014.0492 · Cited by 62 · see citing works
Self-citationMolecular Selection, Modification and Development of Therapeutic Oligonucleotide Aptamers
Yu, Y., Liang, C., Lv, Q., Li, D., Xu, X., Liu, B.-Q., Lü, A., & Zhang, G. (2016) · International Journal of Molecular Sciences · doi:10.3390/ijms17030358 · Cited by 60 · see citing works
Advances in structure-switching aptasensing towards real time detection of cytokines
Cao, C., Zhang, F., Goldys, E. M., Gao, F., & Liu, G. (2018) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2018.03.002 · Cited by 60 · see citing works
Prediction of Aptamer-Target Interacting Pairs with Pseudo-Amino Acid Composition
Li, B., Zhang, Y., Huang, G., Cui, W., Zhang, N., & Cai, Y. (2014) · PLoS ONE · doi:10.1371/journal.pone.0086729 · Cited by 59 · see citing works
Smart Materials Based on DNA Aptamers: Taking Aptasensing to the Next Level
Mastronardi, E., Foster, A., Zhang, X., & DeRosa, M. C. (2014) · Sensors · doi:10.3390/s140203156 · Cited by 56 · see citing works
Self-citationUsing RNA as Molecular Code for Programming Cellular Function
Kushwaha, M., Rostain, W., Prakash, S., Duncan, J. N., & Jaramillo, A. (2016) · ACS Synthetic Biology · doi:10.1021/acssynbio.5b00297 · Cited by 53 · see citing works
UTexas Aptamer Database: the collection and long-term preservation of aptamer sequence information
Askari, A., Kota, S., Ferrell, H., Swamy, S., Goodman, K. S., Okoro, C. C., Crenshaw, I. C. S., Hernandez, D. K., Oliphant, T. E., Badrayani, A. A., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad959 · Cited by 51 · see citing works
Zhang, L., Zhang, C., Gao, R., Yang, R., & Song, Q. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-1087-5 · Cited by 49 · see citing works
Shin, I., Kang, K., Kim, J., Sel, S., Choi, J., Lee, J., Kang, H. Y., & Song, G. (2023) · BMC Bioinformatics · doi:10.1186/s12859-023-05577-6 · Cited by 47 · see citing works
Luan, Y., Chen, J., ., G. X., Li, C., Ping, H., Ma, Z., & Lu, A. (2014) · Microchimica Acta · doi:10.1007/s00604-014-1420-5 · Cited by 46 · see citing works
RNA Therapeutics: How Far Have We Gone?
Coutinho, M. F., Matos, L., Santos, J. I., & Alves, S. (2019) · Advances in experimental medicine and biology · doi:10.1007/978-3-030-19966-1_7 · Cited by 44 · see citing works
Prediction of aptamer affinity using an artificial intelligence approach
Fallah, A., Havaei, S. A., Sedighian, H., Kachuei, R., & Fooladi, A. A. I. (2024) · Journal of Materials Chemistry B · doi:10.1039/d4tb00909f · Cited by 42 · see citing works
Computational predictive approaches for interaction and structure of aptamers
Emami, N., Pakchin, P. S., & Ferdousi, R. (2020) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2020.110268 · Cited by 39 · see citing works
In vitro selection of aptamers and their applications
DeRosa, M. C., Lin, A., Mallikaratchy, P. R., McConnell, E. M., McKeague, M., Patel, R. M., & Shigdar, S. L. (2023) · Nature Reviews Methods Primers · doi:10.1038/s43586-023-00247-6 · Cited by 37 · see citing works
Self-citationValenzano, S., Girolamo, A. D., DeRosa, M. C., McKeague, M., Schena, R., Catucci, L., & Pascale, M. (2016) · ACS Combinatorial Science · doi:10.1021/acscombsci.5b00163 · Cited by 36 · see citing works
Self-citationDevelopment of a DNA aptamer for direct and selective homocysteine detection in human serum
McKeague, M., Foster, A., Miguel, Y., Giamberardino, A., Verdin, C., Chan, J. Y. S., & DeRosa, M. C. (2013) · RSC Advances · doi:10.1039/c3ra43893g · Cited by 35 · see citing works
Self-citationTruncations and in silico docking to enhance the analytical response of aptamer-based biosensors
Nguyen, M., Osborne, M., Prevot, G. T., Churcher, Z. R., Johnson, P. E., Simine, L., & Dauphin‐Ducharme, P. (2024) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2024.116680 · Cited by 34 · see citing works
In vitro selection of antibiotic-binding aptamers
Groher, F., & Suess, B. (2016) · Methods · doi:10.1016/j.ymeth.2016.05.008 · Cited by 34 · see citing works
Recent advances in optical aptasensor technology for amplification strategies in cancer diagnostics
Kou, X., Zhang, X., Shao, X., Jiang, C., & Ning, L. (2020) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-020-02774-7 · Cited by 34 · see citing works
Self-citationLiu, H., Luan, Y., Lu, A., Li, B., Yang, M., & Wang, J. (2017) · Microchimica Acta · doi:10.1007/s00604-017-2591-7 · Cited by 33 · see citing works
Lee, G., Jang, G. H., Kang, H. Y., & Song, G. (2021) · PLoS ONE · doi:10.1371/journal.pone.0253760 · Cited by 32 · see citing works
Grußmayer, K. S., Yserentant, K., & Herten, D. (2018) · Methods and Applications in Fluorescence · doi:10.1088/2050-6120/aaf2eb · Cited by 31 · see citing works
Antimicrobial Aptamers for Detection and Inhibition of Microbial Pathogen Growth
Özalp, V. C., Bilecen, K., Kavruk, M., & Öktem, H. A. (2013) · Future Microbiology · doi:10.2217/fmb.12.149 · Cited by 28 · see citing works
PPAI: a web server for predicting protein-aptamer interactions
Li, J., Ma, X., Li, X., & Gu, J. (2020) · BMC Bioinformatics · doi:10.1186/s12859-020-03574-7 · Cited by 26 · see citing works
Wang, S., Zhang, Y., Lu, J., Cui, W., Hu, J., & Cai, Y. (2016) · BioMed Research International · doi:10.1155/2016/8351204 · Cited by 24 · see citing works
A rational approach for generating cardiac troponin I selective Spiegelmers
Szeitner, Z., Lautner, G., Nagy, S. K., Gyurcsányi, R. E., & Mészáros, T. (2014) · Chemical Communications · doi:10.1039/c4cc00447g · Cited by 20 · see citing works
Rosch, J. C., Neal, E. H., Balikov, D. A., Rahim, M., & Lippmann, E. S. (2020) · Cellular and Molecular Bioengineering · doi:10.1007/s12195-020-00651-y · Cited by 20 · see citing works
Oteng, E. K., Gu, W., & McKeague, M. (2020) · Scientific Reports · doi:10.1038/s41598-020-66537-1 · Cited by 18 · see citing works
Self-citationFunctional nucleic acid-based biosensors for virus detection
Zhang, Z., Adhikari, B. R., Sen, P., Soleymani, L., & Li, Y. (2023) · Advanced Agrochem · doi:10.1016/j.aac.2023.07.006 · Cited by 17 · see citing works
Nanotechnology Meets the Tumor Microenvironment: Unlocking New Horizons in Cancer Therapy
Yadav, P., Yadav, A. K., & Bhatia, D. D. (2025) · ACS Biomaterials Science & Engineering · doi:10.1021/acsbiomaterials.5c01120 · Cited by 16 · see citing works
APIPred: An XGBoost-Based Method for Predicting Aptamer–Protein Interactions
Fang, Z., Wu, Z., Wu, X., Chen, S., Wang, X., Umrao, S., & Dwivedy, A. (2023) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.3c00713 · Cited by 15 · see citing works
Constructive Prediction of Potential RNA Aptamers for a Protein Target
Lee, W., & Han, K. (2019) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2019.2951114 · Cited by 12 · see citing works
Prediction of Aptamer Protein Interaction Using Random Forest Algorithm
Manju, N., Samiha, C. M., Kumar, S. P. P., Gururaj, H. L., & Flammini, F. (2022) · IEEE Access · doi:10.1109/access.2022.3172278 · Cited by 12 · see citing works
The Influence of Protein Charge and Molecular Weight on the Affinity of Aptamers
Drees, A., Trinh, T. L., & Fischer, M. J. (2023) · Pharmaceuticals · doi:10.3390/ph16030457 · Cited by 11 · see citing works
Ribocentre-aptamer: an integrative, structure-focused database for RNA aptamers
Lu, Z., Sun, H. X., Fu, B., Ao, Y., Wang, J., Chen, K., Luo, Y., Li, L., Qiu, Z., Zhao, J., et al. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf1016 · Cited by 13 · see citing works
Recent advances in biocuration: Meeting Report from the fifth International Biocuration Conference
Gaudet, P., Arighi, C. N., Bastian, F., Bateman, A. G., Blake, J. A., Cherry, J. M., D’Eustachio, P., Finn, R. D., Giglio, M. G., Hirschman, L., et al. (2012) · Database · doi:10.1093/database/bas036 · Cited by 11 · see citing works
Applications and modifications of aptamers: potential tool for medical microbiology
Fooladi, A. A. I., Hedayati, M., Amin, M., & Amani, J. (2016) · Reviews in Medical Microbiology · doi:10.1097/mrm.0000000000000064 · Cited by 9 · see citing works
Jain, P., Tiwari, A. K., & Som, T. (2024) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-024-04837-4 · Cited by 7 · see citing works
TFIDF-Random Forest: Prediction of Aptamer-Protein Interacting Pairs
Uwiragiye, E., & Rhinehardt, K. L. (2021) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2021.3098709 · Cited by 7 · see citing works
Antibody‐Functionalized DNA Hydrogels Recognize and Isolate Living Tumor Cells
Bourdon, L., Cochard, A., Tauran, Y., Sugitani, Y., Sato, Y., Takinoue, M., Fujita, H., Fujii, T., Kim, S. H., & Genot, A. J. (2025) · Advanced Materials Interfaces · doi:10.1002/admi.202500619 · Cited by 5 · see citing works
Evolutionary Engineering for Industrial Microbiology
Vanee, N., Fisher, A. B., & Fong, S. S. (2012) · Sub-cellular biochemistry/Subcellular biochemistry · doi:10.1007/978-94-007-5055-5_3 · Cited by 5 · see citing works
Samhitha, S. S., Surabhi, S., Quezada, C., Ges, A., Melendrez, M. F., Sanchez, G., & Morales, J. O. (2025) · Materials Today Chemistry · doi:10.1016/j.mtchem.2025.102843 · Cited by 4 · see citing works
Progress in graphene-based optical and electrochemical aptasensors
Zhang, X., Zhang, Y., & DeRosa, M. C. (2016) · Elsevier eBooks · doi:10.1016/b978-0-323-42861-3.00013-3 · Cited by 4 · see citing works
Self-citationMokgopa, K. P., Oloniiju, S. D., Lobb, K. A., & Tshiwawa, T. (2025) · BioTech · doi:10.3390/biotech14030072 · Cited by 3 · see citing works
Artificial Intelligence for Nucleic Acid Aptamers: Methods and Applications
Liu, S., ZHANG, H.-Q., Ru-Ming, L. I. U., Hong-Juan, Z. E. N. G., Deng, K., Yan, D., Tang, L.-X., & Lin, H. (2025) · PROGRESS IN BIOCHEMISTRY AND BIOPHYSICS · doi:10.3724/j.pibb.2025.0355 · Cited by 3 · see citing works
White, T. M. (2017) · KU ScholarWorks (The University of Kansas) · Cited by 3 · see citing works
Zhang, J., Yan, Z., Zeng, H., & Zhu, Z. (2024) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm62325.2024.10822859 · Cited by 2 · see citing works
Tripathi, A., Vaishnaw, B., Jaishwal, P., Samal, P. K., Verma, A., & Singh, N. (2025) · Current Materials Science · doi:10.2174/0126661454366845250618053301 · Cited by 2 · see citing works
Meyer, C., Hahn, U., & Torda, A. E. (2013) · Wiley eBooks · doi:10.1002/9783527677016.ch21 · Cited by 2 · see citing works
Modern Methods of Molecular Modeling of Aptamers
Kudryashova, N., Долгушева, В. А., Dobrokhotov, I. V., Nasayev, S. S., & Moskalev, A. A. (2026) · Molecular Biology · doi:10.1134/s0026893326700019 · Cited by 1 · see citing works
Neural Network-Based Prediction of Potential Ribonucleic Acid Aptamers to Target Protein
Mahmood, M. A., Malik, H., Khan, A. H., Adnan, M., & Khan, M. I. A. (2022) · Journal of Computing & Biomedical Informatics · doi:10.56979/401/2022/95 · Cited by 1 · see citing works
Chharia, A., Saran, R., & Narayan, A. (2023) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn54540.2023.10191809 · Cited by 1 · see citing works
InChemicoModification of Nucleotides for Better Recognition
Jurek, P., Matusiewicz, M., Mazurek, M., & Jeleń, F. (2018) · Wiley eBooks · doi:10.1002/9783527806799.ch2 · Cited by 1 · see citing works
Gold Nanoparticles as a Platform for Small Molecule SELEX
Smith, M. (2017) · doi:10.22215/etd/2017-11904 · Cited by 1 · see citing works
DNA/Metal Oxide Nanoconjugates: Fundamental Understandings and Analytical Applications
Liu, B. (2016) · UWSpace (University of Waterloo)
Finding Potential RNA Aptamers for a Protein Target Using Sequence and Structure Features
Lee, W., Lee, J., & Han, K. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-95930-6_89
An Investigation into the Structural Basis for Nucleic Acid Small Molecule Binding
Cruz-Toledo, J. (2014) · doi:10.22215/etd/2014-10426
Self-citationDevelopment of a framework to characterise and evolve riboswitches
Jessen, M. X. L. (2023) · Queensland University of Technology · doi:10.5204/thesis.eprints.237756
Integrated Microfluidic Biosensor Platforms for Bioanalytical and Environmental Applications
Pilli, S., & Dasari, P. R. (2024) · Nanotechnology in the life sciences · doi:10.1007/978-3-031-72004-8_14
Mehrzad, A., Rouhbakhskh, Z., Verdian, A., & Negahdary, M. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-13633-7.00012-0
Additional file 2 of PPAI: a web server for predicting protein-aptamer interactions
Li, J., Ma, X., Li, X., & Gu, J. (2020) · Figshare · doi:10.6084/m9.figshare.12457034
Hsu, M.-K., Zeng, Y.-J., Lin, Y., Chen, P., & Wang, H.-Y. (2026) · Journal of the Chinese Chemical Society · doi:10.1002/jccs.70229
Niu, M., Zou, Q., & Xu, L. (2026) · Bioinformatics Advances · doi:10.1093/bioadv/vbag168
AptCancerDB: A Curated Knowledgebase and Translational Discovery Platform for Anticancer AptamersPreprint
Bajiya, N., Singh, S. S., & Raghava, G. P. S. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.07.02.735999 · Cited by 1 · see citing works
APDB: A Large-Scale Repository of Predicted 2D and 3D Aptamer Structures
Mokgopa, K. P., Lobb, K. A., & Tshiwawa, T. (2026) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6c02031
AptViralDB: A repository of experimentally validated antiviral aptamers
Bajiya, N., Singh, S. S., Gahlot, P. S., & Raghava, G. P. S. (2026) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2026.103111
Beyond SELEX: AI-driven aptamers from sequence to structure to function
Cui, B., Lian, X., Song, W., Yang, H., Yang, X., Wang, L., & Yang, G. (2026) · Biotechnology Advances · doi:10.1016/j.biotechadv.2026.109075
- Authors
- Cruz-Toledo, J., McKeague, M., Zhang, X., Giamberardino, A., McConnell, E., Francis, T., DeRosa, M. C., & Dumontier, M.
- Affiliations
- Department of Biology, Carleton University, 2Department of Chemistry, Carleton University, 3Institute of Biochemistry, Department of Biology and Department Chemistry, Carleton University and 4School of Computer Science, Carleton University, 1125 Colonel By Drive, Ottawa, ON, Canada K1S 5B6
- Carleton University (CA)
- Corresponding author
- McKeague, Maureen
- DeRosa, Maria C.
- Dumontier, Michel
- Venue
- Database
- Publisher
- Oxford University Press (OUP)
- Published
- 2012-01-01
- Volume
- 2012
- Pages
- bas006-bas006
- ISSN
- 1758-0463 (ISSN-L)
- PMC
- PMC3308162
- OpenAlex
- W2135504399
- Cited by
- 95
- References
- 39
- Citations by year
- 2026: 7 · 2025: 8 · 2024: 5 · 2023: 10 · 2022: 4 · 2021: 5 · 2020: 6 · 2019: 4 · 2018: 4 · 2017: 6 · 2016: 12 · 2015: 6 · 2014: 7 · 2013: 7 · 2012: 4
- FWCI
- 3.08
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Database (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (acceptedVersion, cc-by-nc)
- Carleton University's Institutional Repository (MacOdrum Library, Carleton University) (submittedVersion, other-oa)
- Research Publications (Maastricht University) (submittedVersion, cc-by-nc)
- Funders
- Natural Sciences and Engineering Research Council of Canada
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced biosensing and bioanalysis techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › DNA and Nucleic Acid Chemistry
- Keywords
- aptamers, SELEX, aptamer selection, knowledge base, binding affinity, molecular recognition, protein-nucleic acid interactions, data curation
- MeSH terms
- Database Management Systems, Research Design, Databases, Factual, SELEX Aptamer Technique, Aptamers, Nucleotide, Aptamers, Peptide
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review