Bibliographic record
Abstract
Today the omnipresence of MS-based proteomic approaches suggest, that 2-dimensional gel (2-DE) based proteomics is dead. In reality, this is far from the truth, and also after three decades high-resolution 2-DE, introduced by Patrick O’Farrell in 1975, still represents a key technology to investigate thousands of protein species, their isoforms and modifications simultaneously. Especially, in combination with multi fluorescence labelling and various MS-methodologies, it is very popular to relatively quantify and identify proteins in complex mixtures. But also after these 30 years of use, reproducibility and process stability are still under constant improvement to further enhance robustness and feasibility of the method. In order to offer an opportunity to discuss and apply the latest developments in 2-DE in a scientific context we picked out this technology as central theme for the International Protein Rainbow Workshop titled ‘‘2-Dimensional Gel Electrophoresis Reloaded’’, which was held at the Institute of Clinical Biochemistry and Pathobiochemistry at the German Diabetes-Center in Duesseldorf. This annual hands-on training course, comprising theoretical and practical aspects of the technology, was accompanied by a lecture day giving an overview of recent 2-DE applications in scientific research. In dependence on this the current issue ‘‘2-Dimensional Gel Electrophoresis Reloaded’’ should help to give an overview of recent developments and applications related to 2-DE. The collection of scientific reports covers a broad range of applications, starting with an inter-laboratory comparison introducing a simplified and robust 2-DE work-flow. In addition a novel fluorescent dye for improved protein detection is described and pre-analytical conditions for serum proteomics, representing one crucial point for biomarker discovery are addressed. Another study examines differences and similarities between protein patterns derived from mitochondria and peroxisomes or describe the characterization of sub-types in small cell lung cancer (SCLC).
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".