High Information Density and Low Coverage Data Storage in DNA with Efficient Channel Coding Schemes Article Swipe
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2410.04886
DNA-based data storage has been attracting significant attention due to its extremely high data storage density, low power consumption, and long duration compared to conventional data storage media. Despite the recent advancements in DNA data storage technology, significant challenges remain. In particular, various types of errors can occur during the processes of DNA synthesis, storage, and sequencing, including substitution errors, insertion errors, and deletion errors. Furthermore, the entire oligo may be lost. In this work, we report a DNA-based data storage architecture that incorporates efficient channel coding schemes, including different types of error-correcting codes (ECCs) and constrained codes, for both the inner coding and outer coding for the DNA data storage channel. We also carried out large scale experiments to validate our proposed DNA-based data storage architecture. Specifically, 1.61 and 1.69 MB data were encoded into 30,000 oligos each, with information densities of 1.731 and 1.815, respectively. It has been found that the stored information can be fully recovered without any error at average coverages of 4.5 and 6.0, respectively. This experiment achieved the highest net information density and lowest coverage among existing DNA-based data storage experiments (with standard DNA), with data recovery rates and coverage approaching theoretical optima.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2410.04886
- https://arxiv.org/pdf/2410.04886
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4403964265
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4403964265Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2410.04886Digital Object Identifier
- Title
-
High Information Density and Low Coverage Data Storage in DNA with Efficient Channel Coding SchemesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-10-07Full publication date if available
- Authors
-
Yijie Ding, Xuan He, Tuan Thanh Nguyen, Wentu Song, Zohar Yakhini, Eitan Yaakobi, Linqiang Pan, Xiaohu Tang, Kui CaiList of authors in order
- Landing page
-
https://arxiv.org/abs/2410.04886Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2410.04886Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2410.04886Direct OA link when available
- Concepts
-
Coding (social sciences), Channel (broadcasting), Computer science, Channel code, Computer network, Telecommunications, Mathematics, Decoding methods, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4403964265 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.2410.04886 |
| ids.doi | https://doi.org/10.48550/arxiv.2410.04886 |
| ids.openalex | https://openalex.org/W4403964265 |
| fwci | |
| type | preprint |
| title | High Information Density and Low Coverage Data Storage in DNA with Efficient Channel Coding Schemes |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T12029 |
| topics[0].field.id | https://openalex.org/fields/13 |
| topics[0].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[0].score | 0.9994999766349792 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1312 |
| topics[0].subfield.display_name | Molecular Biology |
| topics[0].display_name | DNA and Biological Computing |
| topics[1].id | https://openalex.org/T10682 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9786999821662903 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1702 |
| topics[1].subfield.display_name | Artificial Intelligence |
| topics[1].display_name | Quantum Computing Algorithms and Architecture |
| topics[2].id | https://openalex.org/T10207 |
| topics[2].field.id | https://openalex.org/fields/13 |
| topics[2].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[2].score | 0.9782999753952026 |
| topics[2].domain.id | https://openalex.org/domains/1 |
| topics[2].domain.display_name | Life Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1312 |
| topics[2].subfield.display_name | Molecular Biology |
| topics[2].display_name | Advanced biosensing and bioanalysis techniques |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C179518139 |
| concepts[0].level | 2 |
| concepts[0].score | 0.5567822456359863 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q5140297 |
| concepts[0].display_name | Coding (social sciences) |
| concepts[1].id | https://openalex.org/C127162648 |
| concepts[1].level | 2 |
| concepts[1].score | 0.543612003326416 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q16858953 |
| concepts[1].display_name | Channel (broadcasting) |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.4766862392425537 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C166366890 |
| concepts[3].level | 3 |
| concepts[3].score | 0.4352515935897827 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q602136 |
| concepts[3].display_name | Channel code |
| concepts[4].id | https://openalex.org/C31258907 |
| concepts[4].level | 1 |
| concepts[4].score | 0.2850326895713806 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q1301371 |
| concepts[4].display_name | Computer network |
| concepts[5].id | https://openalex.org/C76155785 |
| concepts[5].level | 1 |
| concepts[5].score | 0.2310703694820404 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q418 |
| concepts[5].display_name | Telecommunications |
| concepts[6].id | https://openalex.org/C33923547 |
| concepts[6].level | 0 |
| concepts[6].score | 0.1830405294895172 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[6].display_name | Mathematics |
| concepts[7].id | https://openalex.org/C57273362 |
| concepts[7].level | 2 |
| concepts[7].score | 0.18093889951705933 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q576722 |
| concepts[7].display_name | Decoding methods |
| concepts[8].id | https://openalex.org/C105795698 |
| concepts[8].level | 1 |
| concepts[8].score | 0.1154451072216034 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[8].display_name | Statistics |
| keywords[0].id | https://openalex.org/keywords/coding |
| keywords[0].score | 0.5567822456359863 |
| keywords[0].display_name | Coding (social sciences) |
| keywords[1].id | https://openalex.org/keywords/channel |
| keywords[1].score | 0.543612003326416 |
| keywords[1].display_name | Channel (broadcasting) |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.4766862392425537 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/channel-code |
| keywords[3].score | 0.4352515935897827 |
| keywords[3].display_name | Channel code |
| keywords[4].id | https://openalex.org/keywords/computer-network |
| keywords[4].score | 0.2850326895713806 |
| keywords[4].display_name | Computer network |
| keywords[5].id | https://openalex.org/keywords/telecommunications |
| keywords[5].score | 0.2310703694820404 |
| keywords[5].display_name | Telecommunications |
| keywords[6].id | https://openalex.org/keywords/mathematics |
| keywords[6].score | 0.1830405294895172 |
| keywords[6].display_name | Mathematics |
| keywords[7].id | https://openalex.org/keywords/decoding-methods |
| keywords[7].score | 0.18093889951705933 |
| keywords[7].display_name | Decoding methods |
| keywords[8].id | https://openalex.org/keywords/statistics |
| keywords[8].score | 0.1154451072216034 |
| keywords[8].display_name | Statistics |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:2410.04886 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | https://arxiv.org/pdf/2410.04886 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | text |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://arxiv.org/abs/2410.04886 |
| locations[1].id | doi:10.48550/arxiv.2410.04886 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400194 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | True |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | arXiv (Cornell University) |
| locations[1].source.host_organization | https://openalex.org/I205783295 |
| locations[1].source.host_organization_name | Cornell University |
| locations[1].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | https://doi.org/10.48550/arxiv.2410.04886 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5100688233 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-2911-7643 |
| authorships[0].author.display_name | Yijie Ding |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Ding, Yi |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5101447670 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-0725-3388 |
| authorships[1].author.display_name | Xuan He |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | He, Xuan |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5081533260 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-3179-9471 |
| authorships[2].author.display_name | Tuan Thanh Nguyen |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Nguyen, Tuan Thanh |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5012367423 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-2720-1622 |
| authorships[3].author.display_name | Wentu Song |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Song, Wentu |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5002511176 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-0420-5412 |
| authorships[4].author.display_name | Zohar Yakhini |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Yakhini, Zohar |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5021586372 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-9851-5234 |
| authorships[5].author.display_name | Eitan Yaakobi |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Yaakobi, Eitan |
| authorships[5].is_corresponding | False |
| authorships[6].author.id | https://openalex.org/A5108060216 |
| authorships[6].author.orcid | https://orcid.org/0000-0002-4554-455X |
| authorships[6].author.display_name | Linqiang Pan |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Pan, Linqiang |
| authorships[6].is_corresponding | False |
| authorships[7].author.id | https://openalex.org/A5086776927 |
| authorships[7].author.orcid | https://orcid.org/0009-0008-9305-1945 |
| authorships[7].author.display_name | Xiaohu Tang |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | Tang, Xiaohu |
| authorships[7].is_corresponding | False |
| authorships[8].author.id | https://openalex.org/A5042415594 |
| authorships[8].author.orcid | https://orcid.org/0000-0003-2059-0071 |
| authorships[8].author.display_name | Kui Cai |
| authorships[8].author_position | last |
| authorships[8].raw_author_name | Cai, Kui |
| authorships[8].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/2410.04886 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2024-11-01T00:00:00 |
| display_name | High Information Density and Low Coverage Data Storage in DNA with Efficient Channel Coding Schemes |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T12029 |
| primary_topic.field.id | https://openalex.org/fields/13 |
| primary_topic.field.display_name | Biochemistry, Genetics and Molecular Biology |
| primary_topic.score | 0.9994999766349792 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1312 |
| primary_topic.subfield.display_name | Molecular Biology |
| primary_topic.display_name | DNA and Biological Computing |
| related_works | https://openalex.org/W4391375266, https://openalex.org/W2899084033, https://openalex.org/W2748952813, https://openalex.org/W2390279801, https://openalex.org/W4391913857, https://openalex.org/W2358668433, https://openalex.org/W4396701345, https://openalex.org/W2376932109, https://openalex.org/W2001405890, https://openalex.org/W2545303390 |
| cited_by_count | 0 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:arXiv.org:2410.04886 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://arxiv.org/pdf/2410.04886 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | text |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/2410.04886 |
| primary_location.id | pmh:oai:arXiv.org:2410.04886 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/2410.04886 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | text |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/2410.04886 |
| publication_date | 2024-10-07 |
| publication_year | 2024 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 77 |
| abstract_inverted_index.In | 40, 72 |
| abstract_inverted_index.It | 147 |
| abstract_inverted_index.MB | 131 |
| abstract_inverted_index.We | 112 |
| abstract_inverted_index.at | 162 |
| abstract_inverted_index.be | 70, 156 |
| abstract_inverted_index.in | 32 |
| abstract_inverted_index.of | 44, 51, 91, 142, 165 |
| abstract_inverted_index.to | 9, 23, 119 |
| abstract_inverted_index.we | 75 |
| abstract_inverted_index.4.5 | 166 |
| abstract_inverted_index.DNA | 33, 52, 108 |
| abstract_inverted_index.and | 19, 55, 62, 95, 103, 129, 144, 167, 178, 194 |
| abstract_inverted_index.any | 160 |
| abstract_inverted_index.can | 46, 155 |
| abstract_inverted_index.due | 8 |
| abstract_inverted_index.for | 98, 106 |
| abstract_inverted_index.has | 3, 148 |
| abstract_inverted_index.its | 10 |
| abstract_inverted_index.low | 16 |
| abstract_inverted_index.may | 69 |
| abstract_inverted_index.net | 175 |
| abstract_inverted_index.our | 121 |
| abstract_inverted_index.out | 115 |
| abstract_inverted_index.the | 29, 49, 66, 100, 107, 152, 173 |
| abstract_inverted_index.1.61 | 128 |
| abstract_inverted_index.1.69 | 130 |
| abstract_inverted_index.6.0, | 168 |
| abstract_inverted_index.This | 170 |
| abstract_inverted_index.also | 113 |
| abstract_inverted_index.been | 4, 149 |
| abstract_inverted_index.both | 99 |
| abstract_inverted_index.data | 1, 13, 25, 34, 79, 109, 124, 132, 184, 191 |
| abstract_inverted_index.high | 12 |
| abstract_inverted_index.into | 135 |
| abstract_inverted_index.long | 20 |
| abstract_inverted_index.that | 82, 151 |
| abstract_inverted_index.this | 73 |
| abstract_inverted_index.were | 133 |
| abstract_inverted_index.with | 139, 190 |
| abstract_inverted_index.(with | 187 |
| abstract_inverted_index.1.731 | 143 |
| abstract_inverted_index.DNA), | 189 |
| abstract_inverted_index.among | 181 |
| abstract_inverted_index.codes | 93 |
| abstract_inverted_index.each, | 138 |
| abstract_inverted_index.error | 161 |
| abstract_inverted_index.found | 150 |
| abstract_inverted_index.fully | 157 |
| abstract_inverted_index.inner | 101 |
| abstract_inverted_index.large | 116 |
| abstract_inverted_index.lost. | 71 |
| abstract_inverted_index.occur | 47 |
| abstract_inverted_index.oligo | 68 |
| abstract_inverted_index.outer | 104 |
| abstract_inverted_index.power | 17 |
| abstract_inverted_index.rates | 193 |
| abstract_inverted_index.scale | 117 |
| abstract_inverted_index.types | 43, 90 |
| abstract_inverted_index.work, | 74 |
| abstract_inverted_index.(ECCs) | 94 |
| abstract_inverted_index.1.815, | 145 |
| abstract_inverted_index.30,000 | 136 |
| abstract_inverted_index.codes, | 97 |
| abstract_inverted_index.coding | 86, 102, 105 |
| abstract_inverted_index.during | 48 |
| abstract_inverted_index.entire | 67 |
| abstract_inverted_index.errors | 45 |
| abstract_inverted_index.lowest | 179 |
| abstract_inverted_index.media. | 27 |
| abstract_inverted_index.oligos | 137 |
| abstract_inverted_index.recent | 30 |
| abstract_inverted_index.report | 76 |
| abstract_inverted_index.stored | 153 |
| abstract_inverted_index.Despite | 28 |
| abstract_inverted_index.average | 163 |
| abstract_inverted_index.carried | 114 |
| abstract_inverted_index.channel | 85 |
| abstract_inverted_index.density | 177 |
| abstract_inverted_index.encoded | 134 |
| abstract_inverted_index.errors, | 59, 61 |
| abstract_inverted_index.errors. | 64 |
| abstract_inverted_index.highest | 174 |
| abstract_inverted_index.optima. | 198 |
| abstract_inverted_index.remain. | 39 |
| abstract_inverted_index.storage | 2, 14, 26, 35, 80, 110, 125, 185 |
| abstract_inverted_index.various | 42 |
| abstract_inverted_index.without | 159 |
| abstract_inverted_index.achieved | 172 |
| abstract_inverted_index.channel. | 111 |
| abstract_inverted_index.compared | 22 |
| abstract_inverted_index.coverage | 180, 195 |
| abstract_inverted_index.deletion | 63 |
| abstract_inverted_index.density, | 15 |
| abstract_inverted_index.duration | 21 |
| abstract_inverted_index.existing | 182 |
| abstract_inverted_index.proposed | 122 |
| abstract_inverted_index.recovery | 192 |
| abstract_inverted_index.schemes, | 87 |
| abstract_inverted_index.standard | 188 |
| abstract_inverted_index.storage, | 54 |
| abstract_inverted_index.validate | 120 |
| abstract_inverted_index.DNA-based | 0, 78, 123, 183 |
| abstract_inverted_index.attention | 7 |
| abstract_inverted_index.coverages | 164 |
| abstract_inverted_index.densities | 141 |
| abstract_inverted_index.different | 89 |
| abstract_inverted_index.efficient | 84 |
| abstract_inverted_index.extremely | 11 |
| abstract_inverted_index.including | 57, 88 |
| abstract_inverted_index.insertion | 60 |
| abstract_inverted_index.processes | 50 |
| abstract_inverted_index.recovered | 158 |
| abstract_inverted_index.attracting | 5 |
| abstract_inverted_index.challenges | 38 |
| abstract_inverted_index.experiment | 171 |
| abstract_inverted_index.synthesis, | 53 |
| abstract_inverted_index.approaching | 196 |
| abstract_inverted_index.constrained | 96 |
| abstract_inverted_index.experiments | 118, 186 |
| abstract_inverted_index.information | 140, 154, 176 |
| abstract_inverted_index.particular, | 41 |
| abstract_inverted_index.sequencing, | 56 |
| abstract_inverted_index.significant | 6, 37 |
| abstract_inverted_index.technology, | 36 |
| abstract_inverted_index.theoretical | 197 |
| abstract_inverted_index.Furthermore, | 65 |
| abstract_inverted_index.advancements | 31 |
| abstract_inverted_index.architecture | 81 |
| abstract_inverted_index.consumption, | 18 |
| abstract_inverted_index.conventional | 24 |
| abstract_inverted_index.incorporates | 83 |
| abstract_inverted_index.substitution | 58 |
| abstract_inverted_index.Specifically, | 127 |
| abstract_inverted_index.architecture. | 126 |
| abstract_inverted_index.respectively. | 146, 169 |
| abstract_inverted_index.error-correcting | 92 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 9 |
| citation_normalized_percentile |