An in silico study of the genes for the isoflavonoid pathway enzymes in soybean reveals novel expressed homologues
Bibliographic record
Abstract
Soybean [Glycine max (L.) Merr.] is an important source of isoflavones used by the nutraceutical industry. The soybean genome (2n = 40, 975 Mb) has recently been sequenced, and over a million (redundant) gene tags (expressed sequence tags, ESTs) are available in public databases. Using bioinformatics, we investigated five key enzymes of the isoflavonoid pathway (i.e., chalcone isomerase, isoflavone synthase, 2-hydroxyisoflavanone dehydratase, isoflavanone-7-O-glycosyltransferase, and isoflavone-7-O-glucoside-6′′-O-malonyltransferase) to gain a better understanding of which gene homologues are expressed. Contiguous sequences (contigs) were assembled from EST data to represent the specific genes and were subsequently used to predict and verify known and novel gene homologues in the recently released chromosome-based assembly of the soybean genome. Novel transcripts for 2-hydroxyisoflavanone dehydratase and isoflavone-7-O-glucosyltransferase were discovered in these data and in silico expression profiles are presented for all the genes identified in the isoflavonoid pathway. Key words: Soybean, expressed sequence tag, isoflavonoid, gene expression, homologues
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".