(Invited) Single-Molecule Electronic Sensors to Monitor Conformational Dynamics in Nucleic Acids
Bibliographic record
Abstract
Single-molecule biophysics offers unique insight into the dynamics and mechanistics of biomolecules, unlimited by the inevitable averaging associated with ensemble measurements. Apart from established single-molecule characterization techniques based on optical and force spectroscopies, electronic sensors are emerging as a novel approach for single-molecule biophysics. These ultraminiature, point-functionalized circuits offer a powerful method to isolate and probe biomolecules, with the ability to detect tiny changes in charge or conformation over a uniquely wide range of time scales. In particular, we have demonstrated signal acquisition in fast time scales down to the microsecond range, combined with extended, multi-hour measurement times on the same molecule. In this presentation, I will present recent studies exploring the conformational dynamics of nucleic acids. I will demonstrate how nanoelectronic biosensors can detect, through quantized fluctuations in electrical conductance, successive hybridization and melting events in double-stranded DNA, as well as fluctuations between different folded states in single-stranded telomeric DNA and riboswitch RNA sequences. Electronic sensors open the way towards developing integrated genomic analyses, as well as investigating the mechanistic and dynamics landscape of a variety of biomolecules.
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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".