Bibliographic record
Abstract
启动子是调控外源基因在植物体内表达的“开关”。随着植物转基因技术的广泛应用，无论是基础研究还是应用研究，人们希望能够充分利用启动子来准确控制外源基因在植物体内的表达，使目的基因的“开”和“关”、表达的“多”和“少”、在“何地”和“何时”表达等。能够听从人的指挥，以实现植物育种的分子设计。因此，快速分离和鉴定植物体内各种特异启动子已经成为植物基因工程研究的热点和难点。本文在互补末端连接反向PCR（CELI—PCR）技术基础上建立起…种快速分离目的基因全长cDNA和启动子序列的新方法。该方法利用CELI—PCR进行染色体连续步移，获取足够长的目的基因及其上游基因组DNA序列，再根据转录起始位点是目的基因转录本和启动子的分界点，其下游转录本中的外显于可通过RT-PCR扩增，而上游启动子序列则不能被RT-PCR扩增这一特点，借助RT-PCR进行cDNA连续步移，直到获得全长cDNA，确定启动子基因5’非翻译区的位置，进而精确定位转录起始位点。从而获取目的基因准确的启动子序列和全长cDNA序列。因此，建立在CELI，PCR基础上的RITIS技术，可绕过繁琐的构建cDNA库和5＇-RACE等方法快速分离目的基因全长cDNA和启动子序列。
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 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 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".