BGPT: Create Graphs: Rtt109 H3K56Ac evidence map screen vs biochemistry vs phenotype

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Rtt109–H3K56Ac evidence map (screen vs biochemistry vs phenotype)

I can’t yet generate an evidence map with raw-data-backed links (and therefore can’t plot a truthful screen↔biochemistry↔phenotype graph) because I have not been provided the underlying paper set / extracted results for this specific tri-part mapping in this chat context.

What “evidence map” requires

To correctly build the requested comparison, I need the actual experimental evidence units from full-text sources for each node:

Screen: genetic/chemical screens or proteomic/genomic screens implicating RTT109, H3K56 acetylation, or the relevant pathway.
Biochemistry: direct biochemical measurements (e.g., acetyltransferase activity, in vitro/in vivo H3K56Ac abundance, binding/complex formation) tied to Rtt109 and H3K56Ac.
Phenotype: phenotypic assays linked to loss/perturbation of Rtt109 and/or H3K56Ac (e.g., growth, stress sensitivity, DNA damage phenotypes), ideally with genetic epistasis or rescue logic.

Then I can plot an evidence network + a screen→biochemistry→phenotype “bridge strength” view, with inline citations per claim.

Fastest path to completion

Use BGPT’s science agent to locate the relevant full-text, raw experimental results, extract evidence categories (screen/biochemistry/phenotype), and then render the requested Plotly graphs.

Optional: evolve the plan after extraction

What I will output once sources are extracted

Plotly evidence triad map: nodes = studies/experiments; edges = mechanistic linkage; color = evidence type (screen/biochemistry/phenotype).
Bridge-strength plots: (i) screen→biochemistry support; (ii) biochemistry→phenotype support; (iii) overall concordance score.
Evidence table (DataTables): per study, per assay, with directionality (increase/decrease), effect size where available, and limitations.
Critical epistemics**: contradictions, species/model differences, measurement bias, and where conclusions are weak.