Faculty Opinions recommendation of Comprehensive genome-wide protein-DNA interactions detected at single-nucleotide resolution.
Bibliographic record
Abstract
Chromatin immunoprecipitation (ChIP-chip and ChIP-seq) assays identify where proteins bind throughout a genome.However, DNA contamination and DNA fragmentation heterogeneity produce false positives (erroneous calls) and imprecision in mapping.Consequently, stringent data filtering produces false negatives (missed calls).Here we describe ChIP-exo, where an exonuclease trims ChIP DNA to a precise distance from the crosslinking site.Bound locations are detectable as peak-pairs by deep sequencing.Contaminating DNA is degraded or fails to form complementary peak-pairs.With the single bp accuracy provided by ChIP-exo, we show an unprecedented view into genome-wide binding of the yeast transcription factors Reb1, Gal4, Phd1, Rap1, and human CTCF.Each of these factors was chosen to address potential limitations of ChIP-exo.We found that binding sites become unambiguous and reveal diverse tendencies governing in vivo DNA binding specificity that include sequence variants, functionally distinct motifs, motif clustering, secondary interactions, and combinatorial modules within a compound motif.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.050 | 0.056 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".