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Record W3201297415 · doi:10.22215/etd/2019-13862

Functional Applications of Systems Biology Tools: Identification of Novel DNA Repair Factors and Peptide Design

2019· dissertation· en· W3201297415 on OpenAlexaff
Daniel Burnside

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFungal and yeast genetics research
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputational biologyBiologyProteomeSystems biologyProtein–protein interactionFunction (biology)GeneSaccharomyces cerevisiaeGenetics

Abstract

fetched live from OpenAlex

The highly annotated budding yeast Saccharomyces cerevisiae has emerged as the primary model for systems biology, the study of how individual cellular components function within the context of a dynamic cellular system.Several genome/proteomescale tools developed using the S. cerevisiae model have produced extensive information on gene function and interaction networks that is stored in publicly accessible databases.Bioinformatic tools can exploit these databases to infer novel biological activity but these predictions must be tested in functioning cellular systems to assess the effectiveness of any method.The work herein uses systems-based computational tools to make predictions on novel protein/gene function that are tested using yeast functional genomic approaches.This thesis describes the development and validation of a new tool to design synthetic binding proteins that bind to and inhibit targeted yeast proteins Psk1 and Pin4 as well as the identification and functional analysis of three yeast DNA repair genes, PSK1, ARP6, and DEF1.The in-silico protein synthesizer, InSiPS successfully engineered two synthetic proteins known as anti-Psk1 and anti-Pin4.This demonstrated the ability of our approach to translate from computational prediction, to a specific biological interaction and importantly, a functionally significant phenotype.Chemical-genetic interaction analysis showed that cells expressing α-Psk1 and α-Pin4 phenocopy Δpsk1 and Δpin4 mutants and yeast-twohybrid confirmed binary interactions in vivo while in vitro assays verify that binding is iii occurring at predicted loci.Further analysis of the anti-Psk1/Psk1 interaction motif showed strong, specific binding.Psk1 was inferred to participate in yeast nonhomologous end-joining (NHEJ) repair of double-strand breaks (DSB), an essential DNA repair pathway.Our functional genetic analysis showed that PSK1 is an important novel NHEJ gene that contributes to repair fidelity while appearing to function through RAD27 activity.We also report that ARP6, affects NHEJ through the RSC chromatin remodeling complex.Lastly, we identify new properties of the Def1 DNA repair protein in yeast NHEJ and a physical and genetic interaction between Yku80 and Def1.Together, these findings demonstrate the ability to predict novel gene/protein function using computational tools and expand our understanding of eukaryotic DSB repair.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.043
GPT teacher head0.303
Teacher spread0.259 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2019
Admission routes1
Has abstractyes

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