FootPrinter3: phylogenetic footprinting in partially alignable sequences
Bibliographic record
Abstract
FootPrinter3 is a web server for predicting transcription factor binding sites by using phylogenetic footprinting. Until now, phylogenetic footprinting approaches have been based either on multiple alignment analysis (e.g. PhyloVista, PhastCons), or on motif-discovery algorithms (e.g. FootPrinter2). FootPrinter3 integrates these two approaches, making use of local multiple sequence alignment blocks when those are available and reliable, but also allowing finding motifs in unalignable regions. The result is a set of predictions that joins the advantages of alignment-based methods (good specificity) to those of motif-based methods (good sensitivity, even in the presence of highly diverged species). FootPrinter3 is thus a tool of choice to exploit the wealth of vertebrate genomes being sequenced, as it allows taking full advantage of the sequences of highly diverged species (e.g. chicken, zebrafish), as well as those of more closely related species (e.g. mammals). The FootPrinter3 web server is available at: http://www.mcb.mcgill.ca/~blanchem/FootPrinter3.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.035 | 0.024 |
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".