Finding low-energy conformations of lattice protein models by quantum annealing
Perdomo-Ortiz A, Dickson N, Drew-Brook M, Rose G, Aspuru-Guzik A. · Scientific Reports · 2012
Original publication · Original publication · Original publication
Attributed extracts from the research record
“Lattice protein folding models are a cornerstone of computational biophysics.
This first implementation of a biophysical problem paves the way towards studying optimization problems in biophysics and statistical mechanics using quantum devices.”
Evidence and provenance
Chapter Trust Factor uses a minimum of three distinct qualifying studies. Publication records retain their own evidence and assessment.
Study design and assessment
- design
- assessment
- Not recorded
- trust Factor
- score
- 1
- scope
- Paper
- status
- assessed
- randomized Controlled Trial
- Not recorded
- blinding
- not-confirmed
- peer Reviewed
- true
- basis
- Indexed peer-reviewed research; a qualifying randomized controlled design is not established in the reviewed record.
- sources
https://pubmed.ncbi.nlm.nih.gov/22891157/ · https://doi.org/10.1038/srep00571 · https://www.nature.com/articles/srep00571
- review Scope
- Existing publication-specific assessments and bibliographic indexing; no blanket full-text appraisal.
- assessed At
- 2026-10-27
- jadad
- status
- unassessed
- score
- Not recorded
- evidence
- Not recorded
Topics and recorded topic scores
- key
- general:sound-xxviii
- title
- Quantum computing methods for bioinformatics and gene-expression modelling
- collection
- general
- trust Score
- Not recorded
Citation snapshot and identifiers
- id
- pmid-22891157
- doi
- 10.1038/srep00571
- pmid
- 22891157
- citation Snapshot
- Not recorded
- citations By Collection
- general
- 234
Complete approved library record
- id
- pmid-22891157
- publication Key
- Not recorded
- aliases
- None recorded
- title
- Finding low-energy conformations of lattice protein models by quantum annealing
- journal
- Scientific Reports
- publisher Family
- nature
- publisher Family Label
- Nature Portfolio
- neurotransmitters
- None recorded
- year
- 2012
- authors
- Perdomo-Ortiz A, Dickson N, Drew-Brook M, Rose G, Aspuru-Guzik A.
- design
- kind
- Journal article
- identity Conflict
- Not recorded
- doi
- 10.1038/srep00571
- pmid
- 22891157
- urls
https://doi.org/10.1038/srep00571 · https://www.nature.com/articles/srep00571 · https://pubmed.ncbi.nlm.nih.gov/22891157/
- collections
general
- categories
Methods & context
- targets
- None recorded
- priority
- 1
- quotes
“Lattice protein folding models are a cornerstone of computational biophysics. · This first implementation of a biophysical problem paves the way towards studying optimization problems in biophysics and statistical mechanics using quantum devices.”
- summary
- limitation
- citation Count
- 234
- paper Trust Assessment
- score
- 1
- scope
- Paper
- status
- assessed
- randomized Controlled Trial
- Not recorded
- blinding
- not-confirmed
- peer Reviewed
- true
- basis
- Indexed peer-reviewed research; a qualifying randomized controlled design is not established in the reviewed record.
- sources
https://pubmed.ncbi.nlm.nih.gov/22891157/ · https://doi.org/10.1038/srep00571 · https://www.nature.com/articles/srep00571
- review Scope
- Existing publication-specific assessments and bibliographic indexing; no blanket full-text appraisal.
- assessed At
- 2026-10-27
- citations By Collection
- general
- 234
- topics
- key
- general:sound-xxviii
- title
- Quantum computing methods for bioinformatics and gene-expression modelling
- collection
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- Not recorded
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- chapter Entries
- id
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- pmid-22891157
- title
- Finding low-energy conformations of lattice protein models by quantum annealing
- journal
- Scientific Reports
- year
- 2012
- authors
- Perdomo-Ortiz A, Dickson N, Drew-Brook M, Rose G, Aspuru-Guzik A.
- design
- urls
https://doi.org/10.1038/srep00571 · https://www.nature.com/articles/srep00571 · https://pubmed.ncbi.nlm.nih.gov/22891157/
- quotes
- text
- “Lattice protein folding models are a cornerstone of computational biophysics.
- emphasis
- false
- text
- This first implementation of a biophysical problem paves the way towards studying optimization problems in biophysics and statistical mechanics using quantum devices.”
- emphasis
- false
- citation Count
- 234
- source Pages
114
- targets
- None recorded
- categories
Methods & context
- doi
- 10.1038/srep00571
- pmid
- 22891157
- paper Trust Assessment
- score
- 1
- scope
- Paper
- status
- assessed
- randomized Controlled Trial
- Not recorded
- blinding
- not-confirmed
- peer Reviewed
- true
- basis
- Indexed peer-reviewed research; a qualifying randomized controlled design is not established in the reviewed record.
- sources
https://pubmed.ncbi.nlm.nih.gov/22891157/ · https://doi.org/10.1038/srep00571 · https://www.nature.com/articles/srep00571
- review Scope
- Existing publication-specific assessments and bibliographic indexing; no blanket full-text appraisal.
- assessed At
- 2026-10-27
- collection
- general
- chapter Number
- 7
- topic Id
- sound-xxviii
- topic Title
- Quantum computing methods for bioinformatics and gene-expression modelling
- trust Score
- Not recorded
- jadad
- status
- unassessed
- score
- Not recorded
- condition Evidence
- None recorded
- conditions
- None recorded
- topic Trust Scores
- None recorded
- full Text
- status
- not-indexed
- retrieval Available
- false