FunSecKB2: a fungal protein subcellular location knowledgebase
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
FunSecKB2 is an improved and updated version of the fungal secretome and subcellular proteome, i. e. protein subcellular location, knowledgebase. The fungal protein sequence data were retrieved from UniProtKB, consisting of nearly 2 million entries with 167 species having a complete proteome. The assignments of protein subcellular locations were based on curated information and prediction using seven computational tools. The tools used for subcellular location prediction include SignalP, WoLF PSORT, Phobius, TargetP, TMHMM, FragAnchor, and PS-Scan. Secreted proteins, i.e. secretomes, along with 15 other subcellular proteomes were predicted. The database can be searched by users using several different types of identifiers, gene name or keyword(s). A subcellular proteome from a species can be searched or downloaded. BLAST searching whole fungal protein data or secretomes is available. Community annotation of subcelluar locations based on experimental evidence is also supported. A primary analysis revealed that the secretome size of a fungal species is one of the determining factors to its lifestyle. The Gene Ontology and protein domain analysis of fungal secretomes revealed that fungal secretomes contain a large number of hydrolases, peptidases, oxidoreductases, and lysases, which may have potential applications in bio-processing of chemical wastes or biofuel production. The database provides an important and rich resource for the fungal community looking for protein subcellular location information and performing comparative subcellular proteome analysis. Database URL: http://proteomics.ysu.edu/secretomes/fungi2/index.php
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it