ConSpliceML
Splicing constraint and machine-learning meta-score; precomputed scores.
No reviewed evaluations are linked here in this release. See the sources and separately identified configurations below.
Overview
Splicing constraint and machine-learning meta-score; precomputed scores.
Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.
Evaluations and results
0 evaluations · 0 results. Different protocols are not a single leaderboard.
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Source checking is not independent reproduction. Release 2026-10-10-7fcc3e48a123.
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How it works, versions and access
Strengths, limitations and unresolved questions
Evidence
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Evidence table
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Sources and history
Release 2026-10-10-7fcc3e48a123 · Record review: source checked
1 source records and release history
- Benchmarking splice variant prediction algorithms using massively parallel splicing assays · Original source · Genome Biology 24:294, published 2023-12-21; PMC10734170 full-text XML
Technical metadata and extraction receipts
Stable ID: splicing-follow-up-20261009-method-conspliceml
- areas
- dna-genomes
- contexts
- research
- method types
- supervised_machine_learning
- reported name
- ConSpliceML
- entity level
- method
- source locator
- Smith and Kitzman Results 'Comparing bioinformatic predictions with MPSA measured effects' and Methods 'Scoring with eight splice effect predictors'
- missing metadata
- version: reason: inapplicable; note: Family record; versions are on configurations
Related records
- configuration of: ConSpliceML (Smith and Kitzman 2023)