Identification of Mammalian Protein Complexes by Lentiviral-Based Affinity Purification and Mass Spectrometry
Bibliographic record
Abstract
Protein complexes and protein-protein interactions (PPIs) are fundamental for most biological functions. Deciphering the extensive protein interaction networks that occur within cellular contexts has become a logical extension to the human genome project. Proteome-scale interactome analysis of mammalian systems requires efficient methods for accurately detecting PPIs with specific considerations for the intrinsic technical challenges of mammalian genome manipulation. In this chapter, we outline in detail an innovative lentiviral-based functional proteomic approach that can be used to rapidly characterize protein complexes from a broad range of mammalian cell lines. This method integrates the following key features: (1) lentiviral elements for efficient delivery of tagged constructs into mammalian cell lines; (2) site-specific Gateway™ recombination sites for easy cloning; (3) versatile epitope-tagging system for flexible affinity purification strategies; and (4) LC-MS-based protein identification using tandem mass spectrometry.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".