CAZymes-based ranking of fungi (CBRF): an interactive web database for identifying fungi with extrinsic plant biomass degrading abilities
Bibliographic record
Abstract
Abstract Carbohydrate-active enzymes (CAZymes) are industrially important enzymes, which are involved in synthesis and breakdown of carbohydrates. CAZymes secreted by microorganisms especially fungi are widely used in industries. However, identifying an ideal fungal candidate is costly and time-consuming process. In this regard, we have developed a web-database "CAZymes Based Ranking of Fungi (CBRF)", for sorting and selecting an ideal fungal candidate based on their genome-wide distribution of CAZymes. We have retrieved the complete annotated proteomic data of 443 published fungal genomes from JGI-MycoCosm web-repository, for the CBRF web-database construction. CBRF web-database was developed using open source computing programing languages such as MySQL, HTML, CSS, bootstrap, jQuery, JavaScript and Ajax frameworks. CBRF web-database sorts complete annotated list of fungi based on three selection functionalities: (a) to sort either by ascending (or) descending orders; (b) to sort the fungi based on a selected CAZy group and class; (c) to sort fungi based on their individual lignocellulolytic abilities. We have also developed a simple and basic webpage "S-CAZymes" using HTML, CSS and Java script languages. The global search functionality of S-CAZymes enables the users to understand and retrieve information about a specific carbohydrate-active enzyme and its current classification in the corresponding CAZy family. The S-CAZymes is a supporting web page which can be used in complementary with the CBRF web-database (knowing the classification of specific CAZyme in S-CAZyme and use this information further to sort fungi using CBRF web-database). The CBRF web-database and S-CAZymes webpage are hosted through Amazon ® Web Services (AWS) available at http://13.58.192.177/RankEnzymes/about . We strongly believe that CBRF web-database simplifies the process of identifying a suitable fungus both in academics and industries. In future, we intend to update the CBRF web-database with the public release of new annotated fungal genomes.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".