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- Eric Kandel
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AMYPdb patterns β’ CF / Sen / Spe overview (from provided research data)
Note: Only the statistics explicitly included in your provided research data are visualized below. CF/Sen/Spe beyond βCF β₯ 0.9β is not numerically provided, so Sen/Spe graphs cannot be responsibly constructed from the supplied dataset.
Key AMYPdb scale metrics (counts)
Source statistics for these counts are taken directly from the AMYPdb paperβs described database contents and numbers.
Pattern composition: PROSITE vs non-PROSITE patterns
PROSITE patterns = 38; total patterns = 3,621. The βnon-PROSITEβ part is computed as (3,621 β 38) using only the provided totals.
Amyloid proteins: full-length vs fragment sequences
Full-length = 1,063 and fragments = 642 are given as the updated AMYPdb amyloid sequence group (total 1,705).
CF-based filtering: patterns with CF β₯ 0.9
The provided research data includes: total patterns = 3,621 and patterns with CF β₯ 0.9 = 956. CF is one of the fitness metrics (along with Sen and Spe) used to evaluate pattern discrimination in AMYPdbβs described workflow; however, Sen/Spe numeric distributions are not provided here, so they are not plotted.
CF / Sen / Spe overview (what can & cannot be graphed from provided numbers)
This figure is deliberately about data availability (graphability) rather than biology: AMYPdbβs method uses Sen, Spe, and CF to evaluate pattern fitness, but only CF β₯ 0.9 and total pattern counts are included in your supplied research data.
Critical notes (skeptical, evidence-bound)
Graph limitation: Sen and Spe are explicitly mentioned as fitness metrics in AMYPdbβs workflow, but no Sen/Spe numeric values or distributions were supplied in your research data, so I cannot produce accurate Sen/Spe plots without introducing unjustified assumptions.
Derived quantity shown: βNon-PROSITE patternsβ is computed as (total β PROSITE) strictly from the provided totals; it is not a separate measured statistic.
Selection bias risk (general): AMYPdbβs pattern discovery and matching depend on underlying public database content (e.g., UniProtKB/PROSITE/sequence coverage), which can be incomplete or uneven across organisms and families; the provided research data explicitly flags reliance on external database quality and update-dependent coverage.
It computes derived counts (e.g., non-PROSITE patterns as total minus PROSITE, and CF<0.9 as total minus CFβ₯0.9) from the provided AMYPdb statistics, enabling accurate plotted proportions.
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