Bibliographic record
Abstract
Abstract Biological membranes consist of lipids and proteins. The lipids are arranged as a fluid bilayer, and the proteins are either embedded in the lipid or are bound to the membrane surface. Research on membranes has moved from early studies of the lipids and membrane models to the determination of the molecular structure and dynamics of membrane proteins. About one‐third of the human genome encodes membrane proteins. Membrane proteins function as enzymes, receptors, transporters and channels, and mutations in their genes cause many inherited diseases. Membrane proteins are also common drug targets. Key Concepts Membrane proteins make up about one‐third of genomes. Membrane proteins play important roles as enzymes, receptors, transporters and channels. The amino acid sequences of membrane proteins can be deduced from their DNA sequences, leading to the construction of topological models. Membrane proteins can be solubilised and purified using detergents; however, they are difficult to crystallise for structural studies. Intrinsic membrane proteins are embedded in complex lipid bilayers and consist of bundles of hydrophobic transmembrane α‐helicals. Extrinsic membrane proteins are associated with the cytoplasmic side of the membrane. Membrane proteins are glycosylated in eucaryotes and form higher oligomeric structures. Mutations in the genes encoding membrane proteins cause inherited diseases. Most commonly use drugs target membrane proteins. Many membrane proteins remain understudied due to their hydrophobic nature and low expression levels.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.092 | 0.113 |
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".