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Record W3022061183 · doi:10.1038/s41525-020-0128-1

Genes and genomes and unnecessary complexity in precision medicine

2020· review· en· W3022061183 on OpenAlex
Rama S. Singh, Bhagwati P. Gupta

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenpj Genomic Medicine · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsContingencyRelevance (law)BiologyOrganismPrecision medicineComputational biologyEvolutionary biologyComputer scienceGeneticsEpistemology

Abstract

fetched live from OpenAlex

The sequencing of the human genome heralded the new age of 'genetic medicine' and raised the hope of precision medicine facilitating prolonged and healthy lives. Recent studies have dampened this expectation, as the relationships among mutations (termed 'risk factors'), biological processes, and diseases have emerged to be more complex than initially anticipated. In this review, we elaborate upon the nature of the relationship between genotype and phenotype, between chance-laden molecular complexity and the evolution of complex traits, and the relevance of this relationship to precision medicine. Molecular contingency, i.e., chance-driven molecular changes, in conjunction with the blind nature of evolutionary processes, creates genetic redundancy or multiple molecular pathways to the same phenotype; as time goes on, these pathways become more complex, interconnected, and hierarchically integrated. Based on the proposition that gene-gene interactions provide the major source of variation for evolutionary change, we present a theory of molecular complexity and posit that it consists of two parts, necessary and unnecessary complexity, both of which are inseparable and increase over time. We argue that, unlike necessary complexity, comprising all aspects of the organism's genetic program, unnecessary complexity is evolutionary baggage: the result of molecular constraints, historical circumstances, and the blind nature of evolutionary forces. In the short term, unnecessary complexity can give rise to similar risk factors with different genetic backgrounds; in the long term, genes become functionally interconnected and integrated, directly or indirectly, affecting multiple traits simultaneously. We reason that in addition to personal genomics and precision medicine, unnecessary complexity has consequences in evolutionary biology.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.063
GPT teacher head0.345
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it