Emerging Mass Spectrometry-Based Technologies for Analyses of Chromatin Changes: Analysis of Histones and Histone Modifications
Bibliographic record
Abstract
Mass spectrometry (MS) is rapidly becoming an indispensable tool for the analysis of posttranslational modifications (PTMs) of proteins, and particularly histone PTMs that regulate physiological processes. The more traditional bottom-up approach of searching for modifications on peptides rather than intact proteins (top-down) has proven useful for finding phosphorylation, acetylation, and ubiquitination sites. With the use of modern instrumentation and various MS-based techniques, peptides and their PTMs can be characterized in a high-throughput manner while still maintaining high sensitivity and specificity. In complement to bottom-up MS, recent advances in MS technology, such as high-field Fourier transform ion cyclotron resonance (FTICR)-mass spectrometry, have permitted the study of intact proteins and their modifications. On-line and off-line protein separation instruments coupled to FTICR-MS allow the characterization of PTMs previously undetectable with bottom-up approaches. The use of unique fragmentation techniques in FTICR-MS provides a viable option for the study of labile modifications. In this chapter, we provide a detailed description of the analytical tools - mass spectrometry in particular - that are used to characterize modifications on peptides and proteins. We also examine the applicability of these mass spectrometric techniques to the study of PTMs on histones via both the bottom-up and top-down proteomics approaches.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".