Sphinx: merging knowledge-based andab initioapproaches to improve protein loop prediction Article Swipe
Claire Marks
,
Jarosław Nowak
,
Stefan Klostermann
,
Guy Georges
,
James B. Dunbar
,
Jiye Shi
,
Sebastian Kelm
,
Charlotte M. Deane
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1093/bioinformatics/btw823
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1093/bioinformatics/btw823
Motivation Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of fragments are searched to find suitable conformations and ab initio, where conformations are generated computationally. Existing knowledge-based methods only use fragments that are the same length as the target, even though loops of slightly different lengths may adopt similar conformations. Here, we present a novel method, Sphinx, which combines ab initio techniques with the potential extra structural information contained within loops of a different length to improve structure prediction. Results We show that Sphinx is able to generate high-accuracy predictions and decoy sets enriched with near-native loop conformations, performing better than the ab initio algorithm on which it is based. In addition, it is able to provide predictions for every target, unlike some knowledge-based methods. Sphinx can be used successfully for the difficult problem of antibody H3 prediction, outperforming RosettaAntibody, one of the leading H3-specific ab initio methods, both in accuracy and speed. Availability and Implementation Sphinx is available at http://opig.stats.ox.ac.uk/webapps/sphinx. Supplementary information Supplementary data are available at Bioinformatics online.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/bioinformatics/btw823
- https://academic.oup.com/bioinformatics/article-pdf/33/9/1346/25151234/btw823.pdf
- OA Status
- hybrid
- Cited By
- 54
- References
- 62
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2574510864
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2574510864Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1093/bioinformatics/btw823Digital Object Identifier
- Title
-
Sphinx: merging knowledge-based andab initioapproaches to improve protein loop predictionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2017Year of publication
- Publication date
-
2017-01-16Full publication date if available
- Authors
-
Claire Marks, Jarosław Nowak, Stefan Klostermann, Guy Georges, James B. Dunbar, Jiye Shi, Sebastian Kelm, Charlotte M. DeaneList of authors in order
- Landing page
-
https://doi.org/10.1093/bioinformatics/btw823Publisher landing page
- PDF URL
-
https://academic.oup.com/bioinformatics/article-pdf/33/9/1346/25151234/btw823.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://academic.oup.com/bioinformatics/article-pdf/33/9/1346/25151234/btw823.pdfDirect OA link when available
- Concepts
-
Sphinx, Ab initio, Computer science, Loop (graph theory), Function (biology), Algorithm, Artificial intelligence, Physics, Mathematics, Biology, Evolutionary biology, Visual arts, Combinatorics, Quantum mechanics, ArtTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
54Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 2, 2023: 6, 2022: 6, 2021: 12, 2020: 10Per-year citation counts (last 5 years)
- References (count)
-
62Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2574510864 |
|---|---|
| doi | https://doi.org/10.1093/bioinformatics/btw823 |
| ids.doi | https://doi.org/10.1093/bioinformatics/btw823 |
| ids.mag | 2574510864 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/28453681 |
| ids.openalex | https://openalex.org/W2574510864 |
| fwci | 3.74121187 |
| mesh[0].qualifier_ui | |
| mesh[0].descriptor_ui | D000465 |
| mesh[0].is_major_topic | False |
| mesh[0].qualifier_name | |
| mesh[0].descriptor_name | Algorithms |
| mesh[1].qualifier_ui | |
| mesh[1].descriptor_ui | D000818 |
| mesh[1].is_major_topic | False |
| mesh[1].qualifier_name | |
| mesh[1].descriptor_name | Animals |
| mesh[2].qualifier_ui | Q000737 |
| mesh[2].descriptor_ui | D000906 |
| mesh[2].is_major_topic | False |
| mesh[2].qualifier_name | chemistry |
| mesh[2].descriptor_name | Antibodies |
| mesh[3].qualifier_ui | Q000378 |
| mesh[3].descriptor_ui | D000906 |
| mesh[3].is_major_topic | False |
| mesh[3].qualifier_name | metabolism |
| mesh[3].descriptor_name | Antibodies |
| mesh[4].qualifier_ui | Q000379 |
| mesh[4].descriptor_ui | D019295 |
| mesh[4].is_major_topic | False |
| mesh[4].qualifier_name | methods |
| mesh[4].descriptor_name | Computational Biology |
| mesh[5].qualifier_ui | |
| mesh[5].descriptor_ui | D051188 |
| mesh[5].is_major_topic | True |
| mesh[5].qualifier_name | |
| mesh[5].descriptor_name | Knowledge Bases |
| mesh[6].qualifier_ui | |
| mesh[6].descriptor_ui | D008958 |
| mesh[6].is_major_topic | True |
| mesh[6].qualifier_name | |
| mesh[6].descriptor_name | Models, Molecular |
| mesh[7].qualifier_ui | |
| mesh[7].descriptor_ui | D011487 |
| mesh[7].is_major_topic | True |
| mesh[7].qualifier_name | |
| mesh[7].descriptor_name | Protein Conformation |
| mesh[8].qualifier_ui | |
| mesh[8].descriptor_ui | D012984 |
| mesh[8].is_major_topic | True |
| mesh[8].qualifier_name | |
| mesh[8].descriptor_name | Software |
| mesh[9].qualifier_ui | |
| mesh[9].descriptor_ui | D000465 |
| mesh[9].is_major_topic | False |
| mesh[9].qualifier_name | |
| mesh[9].descriptor_name | Algorithms |
| mesh[10].qualifier_ui | |
| mesh[10].descriptor_ui | D000818 |
| mesh[10].is_major_topic | False |
| mesh[10].qualifier_name | |
| mesh[10].descriptor_name | Animals |
| mesh[11].qualifier_ui | Q000737 |
| mesh[11].descriptor_ui | D000906 |
| mesh[11].is_major_topic | False |
| mesh[11].qualifier_name | chemistry |
| mesh[11].descriptor_name | Antibodies |
| mesh[12].qualifier_ui | Q000378 |
| mesh[12].descriptor_ui | D000906 |
| mesh[12].is_major_topic | False |
| mesh[12].qualifier_name | metabolism |
| mesh[12].descriptor_name | Antibodies |
| mesh[13].qualifier_ui | Q000379 |
| mesh[13].descriptor_ui | D019295 |
| mesh[13].is_major_topic | False |
| mesh[13].qualifier_name | methods |
| mesh[13].descriptor_name | Computational Biology |
| mesh[14].qualifier_ui | |
| mesh[14].descriptor_ui | D051188 |
| mesh[14].is_major_topic | True |
| mesh[14].qualifier_name | |
| mesh[14].descriptor_name | Knowledge Bases |
| mesh[15].qualifier_ui | |
| mesh[15].descriptor_ui | D008958 |
| mesh[15].is_major_topic | True |
| mesh[15].qualifier_name | |
| mesh[15].descriptor_name | Models, Molecular |
| mesh[16].qualifier_ui | |
| mesh[16].descriptor_ui | D011487 |
| mesh[16].is_major_topic | True |
| mesh[16].qualifier_name | |
| mesh[16].descriptor_name | Protein Conformation |
| mesh[17].qualifier_ui | |
| mesh[17].descriptor_ui | D012984 |
| mesh[17].is_major_topic | True |
| mesh[17].qualifier_name | |
| mesh[17].descriptor_name | Software |
| type | article |
| title | Sphinx: merging knowledge-based andab initioapproaches to improve protein loop prediction |
| awards[0].id | https://openalex.org/G7743085660 |
| awards[0].funder_id | https://openalex.org/F4320334627 |
| awards[0].display_name | |
| awards[0].funder_award_id | EP/G037280/1 |
| awards[0].funder_display_name | Engineering and Physical Sciences Research Council |
| biblio.issue | 9 |
| biblio.volume | 33 |
| biblio.last_page | 1353 |
| biblio.first_page | 1346 |
| topics[0].id | https://openalex.org/T10602 |
| topics[0].field.id | https://openalex.org/fields/13 |
| topics[0].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[0].score | 0.9993000030517578 |
| 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 | Glycosylation and Glycoproteins Research |
| topics[1].id | https://openalex.org/T11016 |
| topics[1].field.id | https://openalex.org/fields/27 |
| topics[1].field.display_name | Medicine |
| topics[1].score | 0.9987999796867371 |
| topics[1].domain.id | https://openalex.org/domains/4 |
| topics[1].domain.display_name | Health Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2741 |
| topics[1].subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| topics[1].display_name | Monoclonal and Polyclonal Antibodies Research |
| topics[2].id | https://openalex.org/T10044 |
| topics[2].field.id | https://openalex.org/fields/13 |
| topics[2].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[2].score | 0.9984999895095825 |
| 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 | Protein Structure and Dynamics |
| funders[0].id | https://openalex.org/F4320334627 |
| funders[0].ror | https://ror.org/0439y7842 |
| funders[0].display_name | Engineering and Physical Sciences Research Council |
| is_xpac | False |
| apc_list.value | 3618 |
| apc_list.currency | USD |
| apc_list.value_usd | 3618 |
| apc_paid.value | 2132 |
| apc_paid.currency | EUR |
| apc_paid.value_usd | 2299 |
| concepts[0].id | https://openalex.org/C2777299493 |
| concepts[0].level | 2 |
| concepts[0].score | 0.75834721326828 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q151480 |
| concepts[0].display_name | Sphinx |
| concepts[1].id | https://openalex.org/C2781442258 |
| concepts[1].level | 2 |
| concepts[1].score | 0.750282347202301 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q46310 |
| concepts[1].display_name | Ab initio |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.7234315872192383 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C184670325 |
| concepts[3].level | 2 |
| concepts[3].score | 0.6720957159996033 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q512604 |
| concepts[3].display_name | Loop (graph theory) |
| concepts[4].id | https://openalex.org/C14036430 |
| concepts[4].level | 2 |
| concepts[4].score | 0.4152248501777649 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q3736076 |
| concepts[4].display_name | Function (biology) |
| concepts[5].id | https://openalex.org/C11413529 |
| concepts[5].level | 1 |
| concepts[5].score | 0.3842792510986328 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[5].display_name | Algorithm |
| concepts[6].id | https://openalex.org/C154945302 |
| concepts[6].level | 1 |
| concepts[6].score | 0.3369561433792114 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[6].display_name | Artificial intelligence |
| concepts[7].id | https://openalex.org/C121332964 |
| concepts[7].level | 0 |
| concepts[7].score | 0.20027190446853638 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[7].display_name | Physics |
| concepts[8].id | https://openalex.org/C33923547 |
| concepts[8].level | 0 |
| concepts[8].score | 0.13225001096725464 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[8].display_name | Mathematics |
| concepts[9].id | https://openalex.org/C86803240 |
| concepts[9].level | 0 |
| concepts[9].score | 0.09068411588668823 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[9].display_name | Biology |
| concepts[10].id | https://openalex.org/C78458016 |
| concepts[10].level | 1 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q840400 |
| concepts[10].display_name | Evolutionary biology |
| concepts[11].id | https://openalex.org/C153349607 |
| concepts[11].level | 1 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q36649 |
| concepts[11].display_name | Visual arts |
| concepts[12].id | https://openalex.org/C114614502 |
| concepts[12].level | 1 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q76592 |
| concepts[12].display_name | Combinatorics |
| concepts[13].id | https://openalex.org/C62520636 |
| concepts[13].level | 1 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q944 |
| concepts[13].display_name | Quantum mechanics |
| concepts[14].id | https://openalex.org/C142362112 |
| concepts[14].level | 0 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q735 |
| concepts[14].display_name | Art |
| keywords[0].id | https://openalex.org/keywords/sphinx |
| keywords[0].score | 0.75834721326828 |
| keywords[0].display_name | Sphinx |
| keywords[1].id | https://openalex.org/keywords/ab-initio |
| keywords[1].score | 0.750282347202301 |
| keywords[1].display_name | Ab initio |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.7234315872192383 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/loop |
| keywords[3].score | 0.6720957159996033 |
| keywords[3].display_name | Loop (graph theory) |
| keywords[4].id | https://openalex.org/keywords/function |
| keywords[4].score | 0.4152248501777649 |
| keywords[4].display_name | Function (biology) |
| keywords[5].id | https://openalex.org/keywords/algorithm |
| keywords[5].score | 0.3842792510986328 |
| keywords[5].display_name | Algorithm |
| keywords[6].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[6].score | 0.3369561433792114 |
| keywords[6].display_name | Artificial intelligence |
| keywords[7].id | https://openalex.org/keywords/physics |
| keywords[7].score | 0.20027190446853638 |
| keywords[7].display_name | Physics |
| keywords[8].id | https://openalex.org/keywords/mathematics |
| keywords[8].score | 0.13225001096725464 |
| keywords[8].display_name | Mathematics |
| keywords[9].id | https://openalex.org/keywords/biology |
| keywords[9].score | 0.09068411588668823 |
| keywords[9].display_name | Biology |
| language | en |
| locations[0].id | doi:10.1093/bioinformatics/btw823 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S52395412 |
| locations[0].source.issn | 1367-4803, 1367-4811 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | 1367-4803 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Bioinformatics |
| locations[0].source.host_organization | https://openalex.org/P4310311648 |
| locations[0].source.host_organization_name | Oxford University Press |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310311648, https://openalex.org/P4310311647 |
| locations[0].source.host_organization_lineage_names | Oxford University Press, University of Oxford |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://academic.oup.com/bioinformatics/article-pdf/33/9/1346/25151234/btw823.pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Bioinformatics |
| locations[0].landing_page_url | https://doi.org/10.1093/bioinformatics/btw823 |
| locations[1].id | pmid:28453681 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | Bioinformatics (Oxford, England) |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/28453681 |
| locations[2].id | pmh:oai:pubmedcentral.nih.gov:5408792 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S2764455111 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | PubMed Central |
| locations[2].source.host_organization | https://openalex.org/I1299303238 |
| locations[2].source.host_organization_name | National Institutes of Health |
| locations[2].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[2].license | cc-by |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | Text |
| locations[2].license_id | https://openalex.org/licenses/cc-by |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Bioinformatics |
| locations[2].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/5408792 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5006452408 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-5931-2437 |
| authorships[0].author.display_name | Claire Marks |
| authorships[0].countries | GB |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I40120149 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Statistics, University of Oxford, Oxford, UK |
| authorships[0].institutions[0].id | https://openalex.org/I40120149 |
| authorships[0].institutions[0].ror | https://ror.org/052gg0110 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I40120149 |
| authorships[0].institutions[0].country_code | GB |
| authorships[0].institutions[0].display_name | University of Oxford |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Claire Marks |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Statistics, University of Oxford, Oxford, UK |
| authorships[1].author.id | https://openalex.org/A5057068711 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Jarosław Nowak |
| authorships[1].countries | GB |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I40120149 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Statistics, University of Oxford, Oxford, UK |
| authorships[1].institutions[0].id | https://openalex.org/I40120149 |
| authorships[1].institutions[0].ror | https://ror.org/052gg0110 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I40120149 |
| authorships[1].institutions[0].country_code | GB |
| authorships[1].institutions[0].display_name | University of Oxford |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Jaroslaw Nowak |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Department of Statistics, University of Oxford, Oxford, UK |
| authorships[2].author.id | https://openalex.org/A5012853684 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-2092-7124 |
| authorships[2].author.display_name | Stefan Klostermann |
| authorships[2].countries | US |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I55921689 |
| authorships[2].affiliations[0].raw_affiliation_string | Pharma Research and Early Development, Informatics, Roche Innovation Center Munich, Penzberg, DE, Germany |
| authorships[2].institutions[0].id | https://openalex.org/I55921689 |
| authorships[2].institutions[0].ror | https://ror.org/04bthcb08 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I55921689 |
| authorships[2].institutions[0].country_code | US |
| authorships[2].institutions[0].display_name | La Roche College |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Stefan Klostermann |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Pharma Research and Early Development, Informatics, Roche Innovation Center Munich, Penzberg, DE, Germany |
| authorships[3].author.id | https://openalex.org/A5058855855 |
| authorships[3].author.orcid | https://orcid.org/0000-0001-5737-006X |
| authorships[3].author.display_name | Guy Georges |
| authorships[3].countries | US |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I129302853 |
| authorships[3].affiliations[0].raw_affiliation_string | Pharma Research and Early Development, Large Molecule Research, Roche Innovation Center Munich, Penzberg, DE, Germany |
| authorships[3].institutions[0].id | https://openalex.org/I129302853 |
| authorships[3].institutions[0].ror | https://ror.org/011qkaj49 |
| authorships[3].institutions[0].type | company |
| authorships[3].institutions[0].lineage | https://openalex.org/I118019719, https://openalex.org/I129302853 |
| authorships[3].institutions[0].country_code | US |
| authorships[3].institutions[0].display_name | Roche (United States) |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Guy Georges |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Pharma Research and Early Development, Large Molecule Research, Roche Innovation Center Munich, Penzberg, DE, Germany |
| authorships[4].author.id | https://openalex.org/A5076900353 |
| authorships[4].author.orcid | https://orcid.org/0009-0008-6752-1421 |
| authorships[4].author.display_name | James B. Dunbar |
| authorships[4].countries | US |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I129302853 |
| authorships[4].affiliations[0].raw_affiliation_string | Pharma Research and Early Development, Large Molecule Research, Roche Innovation Center Munich, Penzberg, DE, Germany |
| authorships[4].institutions[0].id | https://openalex.org/I129302853 |
| authorships[4].institutions[0].ror | https://ror.org/011qkaj49 |
| authorships[4].institutions[0].type | company |
| authorships[4].institutions[0].lineage | https://openalex.org/I118019719, https://openalex.org/I129302853 |
| authorships[4].institutions[0].country_code | US |
| authorships[4].institutions[0].display_name | Roche (United States) |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | James Dunbar |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Pharma Research and Early Development, Large Molecule Research, Roche Innovation Center Munich, Penzberg, DE, Germany |
| authorships[5].author.id | https://openalex.org/A5078567532 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-9628-8680 |
| authorships[5].author.display_name | Jiye Shi |
| authorships[5].countries | GB |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I4210134054 |
| authorships[5].affiliations[0].raw_affiliation_string | Department of Informatics, UCB Pharma, Slough, UK |
| authorships[5].institutions[0].id | https://openalex.org/I4210134054 |
| authorships[5].institutions[0].ror | https://ror.org/03428qp74 |
| authorships[5].institutions[0].type | company |
| authorships[5].institutions[0].lineage | https://openalex.org/I4210134054, https://openalex.org/I85722119 |
| authorships[5].institutions[0].country_code | GB |
| authorships[5].institutions[0].display_name | UCB Pharma (United Kingdom) |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Jiye Shi |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Department of Informatics, UCB Pharma, Slough, UK |
| authorships[6].author.id | https://openalex.org/A5022515446 |
| authorships[6].author.orcid | https://orcid.org/0000-0001-7146-9322 |
| authorships[6].author.display_name | Sebastian Kelm |
| authorships[6].countries | GB |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I4210134054 |
| authorships[6].affiliations[0].raw_affiliation_string | Department of Informatics, UCB Pharma, Slough, UK |
| authorships[6].institutions[0].id | https://openalex.org/I4210134054 |
| authorships[6].institutions[0].ror | https://ror.org/03428qp74 |
| authorships[6].institutions[0].type | company |
| authorships[6].institutions[0].lineage | https://openalex.org/I4210134054, https://openalex.org/I85722119 |
| authorships[6].institutions[0].country_code | GB |
| authorships[6].institutions[0].display_name | UCB Pharma (United Kingdom) |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Sebastian Kelm |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | Department of Informatics, UCB Pharma, Slough, UK |
| authorships[7].author.id | https://openalex.org/A5015572211 |
| authorships[7].author.orcid | https://orcid.org/0000-0003-1388-2252 |
| authorships[7].author.display_name | Charlotte M. Deane |
| authorships[7].countries | GB |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I40120149 |
| authorships[7].affiliations[0].raw_affiliation_string | Department of Statistics, University of Oxford, Oxford, UK |
| authorships[7].institutions[0].id | https://openalex.org/I40120149 |
| authorships[7].institutions[0].ror | https://ror.org/052gg0110 |
| authorships[7].institutions[0].type | education |
| authorships[7].institutions[0].lineage | https://openalex.org/I40120149 |
| authorships[7].institutions[0].country_code | GB |
| authorships[7].institutions[0].display_name | University of Oxford |
| authorships[7].author_position | last |
| authorships[7].raw_author_name | Charlotte M Deane |
| authorships[7].is_corresponding | True |
| authorships[7].raw_affiliation_strings | Department of Statistics, University of Oxford, Oxford, UK |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://academic.oup.com/bioinformatics/article-pdf/33/9/1346/25151234/btw823.pdf |
| open_access.oa_status | hybrid |
| open_access.any_repository_has_fulltext | False |
| created_date | 2017-01-26T00:00:00 |
| display_name | Sphinx: merging knowledge-based andab initioapproaches to improve protein loop prediction |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10602 |
| primary_topic.field.id | https://openalex.org/fields/13 |
| primary_topic.field.display_name | Biochemistry, Genetics and Molecular Biology |
| primary_topic.score | 0.9993000030517578 |
| 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 | Glycosylation and Glycoproteins Research |
| related_works | https://openalex.org/W1982207645, https://openalex.org/W2952747254, https://openalex.org/W2079104883, https://openalex.org/W2078462251, https://openalex.org/W2616994625, https://openalex.org/W2285278858, https://openalex.org/W4251811912, https://openalex.org/W2029530604, https://openalex.org/W2941377492, https://openalex.org/W2178379997 |
| cited_by_count | 54 |
| counts_by_year[0].year | 2024 |
| counts_by_year[0].cited_by_count | 2 |
| counts_by_year[1].year | 2023 |
| counts_by_year[1].cited_by_count | 6 |
| counts_by_year[2].year | 2022 |
| counts_by_year[2].cited_by_count | 6 |
| counts_by_year[3].year | 2021 |
| counts_by_year[3].cited_by_count | 12 |
| counts_by_year[4].year | 2020 |
| counts_by_year[4].cited_by_count | 10 |
| counts_by_year[5].year | 2019 |
| counts_by_year[5].cited_by_count | 9 |
| counts_by_year[6].year | 2018 |
| counts_by_year[6].cited_by_count | 6 |
| counts_by_year[7].year | 2017 |
| counts_by_year[7].cited_by_count | 3 |
| locations_count | 3 |
| best_oa_location.id | doi:10.1093/bioinformatics/btw823 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S52395412 |
| best_oa_location.source.issn | 1367-4803, 1367-4811 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | 1367-4803 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Bioinformatics |
| best_oa_location.source.host_organization | https://openalex.org/P4310311648 |
| best_oa_location.source.host_organization_name | Oxford University Press |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310311648, https://openalex.org/P4310311647 |
| best_oa_location.source.host_organization_lineage_names | Oxford University Press, University of Oxford |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://academic.oup.com/bioinformatics/article-pdf/33/9/1346/25151234/btw823.pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Bioinformatics |
| best_oa_location.landing_page_url | https://doi.org/10.1093/bioinformatics/btw823 |
| primary_location.id | doi:10.1093/bioinformatics/btw823 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S52395412 |
| primary_location.source.issn | 1367-4803, 1367-4811 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | 1367-4803 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Bioinformatics |
| primary_location.source.host_organization | https://openalex.org/P4310311648 |
| primary_location.source.host_organization_name | Oxford University Press |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310311648, https://openalex.org/P4310311647 |
| primary_location.source.host_organization_lineage_names | Oxford University Press, University of Oxford |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://academic.oup.com/bioinformatics/article-pdf/33/9/1346/25151234/btw823.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Bioinformatics |
| primary_location.landing_page_url | https://doi.org/10.1093/bioinformatics/btw823 |
| publication_date | 2017-01-16 |
| publication_year | 2017 |
| referenced_works | https://openalex.org/W419268931, https://openalex.org/W2170471837, https://openalex.org/W2141082242, https://openalex.org/W2067484689, https://openalex.org/W1580407891, https://openalex.org/W2005140643, https://openalex.org/W1982679430, https://openalex.org/W2322339762, https://openalex.org/W2166103775, https://openalex.org/W1998586260, https://openalex.org/W2140508442, https://openalex.org/W2110890402, https://openalex.org/W2077977162, https://openalex.org/W2158999434, https://openalex.org/W2110505462, https://openalex.org/W2116275717, https://openalex.org/W1867795087, https://openalex.org/W1871470604, https://openalex.org/W1980374511, https://openalex.org/W2122943946, https://openalex.org/W2085144661, https://openalex.org/W2102379449, https://openalex.org/W2039885142, https://openalex.org/W2129153475, https://openalex.org/W1913436096, https://openalex.org/W2126103104, https://openalex.org/W1972438493, https://openalex.org/W2117012297, https://openalex.org/W2106648157, https://openalex.org/W2132514101, https://openalex.org/W2167833742, https://openalex.org/W2474661075, https://openalex.org/W2053872195, https://openalex.org/W1995941554, https://openalex.org/W2103741674, https://openalex.org/W2083028331, https://openalex.org/W2110036226, https://openalex.org/W2007804411, https://openalex.org/W2060289095, https://openalex.org/W2155212694, https://openalex.org/W2139475477, https://openalex.org/W1984259239, https://openalex.org/W2074231493, https://openalex.org/W2293719487, https://openalex.org/W2104078482, https://openalex.org/W2078245108, https://openalex.org/W2158307923, https://openalex.org/W2161776897, https://openalex.org/W2002447403, https://openalex.org/W2076694118, https://openalex.org/W2071200955, https://openalex.org/W2036499039, https://openalex.org/W1970858396, https://openalex.org/W2159599720, https://openalex.org/W1967644381, https://openalex.org/W1974596630, https://openalex.org/W2153153865, https://openalex.org/W1996581857, https://openalex.org/W2166021114, https://openalex.org/W2047163848, https://openalex.org/W2578150941, https://openalex.org/W2024969564 |
| referenced_works_count | 62 |
| abstract_inverted_index.a | 77, 96 |
| abstract_inverted_index.H3 | 160 |
| abstract_inverted_index.In | 134 |
| abstract_inverted_index.We | 104 |
| abstract_inverted_index.ab | 42, 83, 126, 169 |
| abstract_inverted_index.as | 60 |
| abstract_inverted_index.at | 183, 191 |
| abstract_inverted_index.be | 25, 151 |
| abstract_inverted_index.in | 173 |
| abstract_inverted_index.is | 108, 132, 137, 181 |
| abstract_inverted_index.it | 131, 136 |
| abstract_inverted_index.of | 33, 66, 95, 158, 165 |
| abstract_inverted_index.on | 129 |
| abstract_inverted_index.to | 16, 37, 99, 110, 139 |
| abstract_inverted_index.we | 75 |
| abstract_inverted_index.and | 41, 114, 175, 178 |
| abstract_inverted_index.are | 3, 35, 46, 56, 189 |
| abstract_inverted_index.can | 23, 150 |
| abstract_inverted_index.for | 6, 142, 154 |
| abstract_inverted_index.may | 70 |
| abstract_inverted_index.one | 164 |
| abstract_inverted_index.the | 57, 61, 87, 125, 155, 166 |
| abstract_inverted_index.two | 28 |
| abstract_inverted_index.use | 53 |
| abstract_inverted_index.able | 109, 138 |
| abstract_inverted_index.both | 172 |
| abstract_inverted_index.data | 188 |
| abstract_inverted_index.even | 63 |
| abstract_inverted_index.find | 38 |
| abstract_inverted_index.into | 27 |
| abstract_inverted_index.loop | 20, 120 |
| abstract_inverted_index.make | 13 |
| abstract_inverted_index.only | 52 |
| abstract_inverted_index.same | 58 |
| abstract_inverted_index.sets | 116 |
| abstract_inverted_index.show | 105 |
| abstract_inverted_index.some | 146 |
| abstract_inverted_index.than | 124 |
| abstract_inverted_index.that | 55, 106 |
| abstract_inverted_index.them | 14 |
| abstract_inverted_index.used | 152 |
| abstract_inverted_index.with | 86, 118 |
| abstract_inverted_index.Here, | 74 |
| abstract_inverted_index.Loops | 2 |
| abstract_inverted_index.adopt | 71 |
| abstract_inverted_index.decoy | 115 |
| abstract_inverted_index.every | 143 |
| abstract_inverted_index.extra | 89 |
| abstract_inverted_index.loops | 65, 94 |
| abstract_inverted_index.model | 17 |
| abstract_inverted_index.novel | 78 |
| abstract_inverted_index.often | 4 |
| abstract_inverted_index.their | 10 |
| abstract_inverted_index.vital | 5 |
| abstract_inverted_index.where | 31, 44 |
| abstract_inverted_index.which | 81, 130 |
| abstract_inverted_index.Sphinx | 107, 149, 180 |
| abstract_inverted_index.based. | 133 |
| abstract_inverted_index.better | 123 |
| abstract_inverted_index.initio | 84, 127, 170 |
| abstract_inverted_index.length | 59, 98 |
| abstract_inverted_index.mostly | 24 |
| abstract_inverted_index.speed. | 176 |
| abstract_inverted_index.though | 64 |
| abstract_inverted_index.unlike | 145 |
| abstract_inverted_index.within | 93 |
| abstract_inverted_index.Current | 19 |
| abstract_inverted_index.Results | 103 |
| abstract_inverted_index.Sphinx, | 80 |
| abstract_inverted_index.divided | 26 |
| abstract_inverted_index.improve | 100 |
| abstract_inverted_index.initio, | 43 |
| abstract_inverted_index.leading | 167 |
| abstract_inverted_index.lengths | 69 |
| abstract_inverted_index.method, | 79 |
| abstract_inverted_index.methods | 51 |
| abstract_inverted_index.online. | 193 |
| abstract_inverted_index.present | 76 |
| abstract_inverted_index.problem | 157 |
| abstract_inverted_index.protein | 7 |
| abstract_inverted_index.provide | 140 |
| abstract_inverted_index.similar | 72 |
| abstract_inverted_index.target, | 62, 144 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Existing | 49 |
| abstract_inverted_index.accuracy | 174 |
| abstract_inverted_index.antibody | 159 |
| abstract_inverted_index.combines | 82 |
| abstract_inverted_index.enriched | 117 |
| abstract_inverted_index.generate | 111 |
| abstract_inverted_index.however, | 9 |
| abstract_inverted_index.methods, | 171 |
| abstract_inverted_index.methods. | 148 |
| abstract_inverted_index.searched | 36 |
| abstract_inverted_index.slightly | 67 |
| abstract_inverted_index.suitable | 39 |
| abstract_inverted_index.addition, | 135 |
| abstract_inverted_index.algorithm | 128 |
| abstract_inverted_index.available | 182, 190 |
| abstract_inverted_index.contained | 92 |
| abstract_inverted_index.databases | 32 |
| abstract_inverted_index.different | 68, 97 |
| abstract_inverted_index.difficult | 15, 156 |
| abstract_inverted_index.fragments | 34, 54 |
| abstract_inverted_index.function, | 8 |
| abstract_inverted_index.generated | 47 |
| abstract_inverted_index.irregular | 11 |
| abstract_inverted_index.modelling | 21 |
| abstract_inverted_index.potential | 88 |
| abstract_inverted_index.structure | 101 |
| abstract_inverted_index.Motivation | 1 |
| abstract_inverted_index.algorithms | 22 |
| abstract_inverted_index.performing | 122 |
| abstract_inverted_index.structural | 90 |
| abstract_inverted_index.structures | 12 |
| abstract_inverted_index.techniques | 85 |
| abstract_inverted_index.H3-specific | 168 |
| abstract_inverted_index.accurately. | 18 |
| abstract_inverted_index.categories: | 29 |
| abstract_inverted_index.information | 91, 186 |
| abstract_inverted_index.near-native | 119 |
| abstract_inverted_index.prediction, | 161 |
| abstract_inverted_index.prediction. | 102 |
| abstract_inverted_index.predictions | 113, 141 |
| abstract_inverted_index.Availability | 177 |
| abstract_inverted_index.successfully | 153 |
| abstract_inverted_index.Supplementary | 185, 187 |
| abstract_inverted_index.conformations | 40, 45 |
| abstract_inverted_index.high-accuracy | 112 |
| abstract_inverted_index.outperforming | 162 |
| abstract_inverted_index.Bioinformatics | 192 |
| abstract_inverted_index.Implementation | 179 |
| abstract_inverted_index.conformations, | 121 |
| abstract_inverted_index.conformations. | 73 |
| abstract_inverted_index.knowledge-based | 50, 147 |
| abstract_inverted_index.RosettaAntibody, | 163 |
| abstract_inverted_index.computationally. | 48 |
| abstract_inverted_index.knowledge-based, | 30 |
| abstract_inverted_index.http://opig.stats.ox.ac.uk/webapps/sphinx. | 184 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 94 |
| corresponding_author_ids | https://openalex.org/A5015572211 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 8 |
| corresponding_institution_ids | https://openalex.org/I40120149 |
| citation_normalized_percentile.value | 0.92091256 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |