skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Search for: All records

Creators/Authors contains: "John, Malcolm"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Despite their lack of a rigid structure, intrinsically disordered regions (IDRs) in proteins play important roles in cellular functions, including mediating protein-protein interactions. Therefore, it is important to computationally annotate IDRs with high accuracy. In this study, we present Disordered Region prediction using Bidirectional Encoder Representations from Transformers (DR-BERT), a compact protein language model. Unlike most popular tools, DR-BERT is pretrained on unannotated proteins and trained to predict IDRs without relying on explicit evolutionary or biophysical data. Despite this, DR-BERT demonstrates significant improvement over existing methods on the Critical Assessment of protein Intrinsic Disorder (CAID) evaluation dataset and outperforms competitors on two out of four test cases in the CAID 2 dataset, while maintaining competitiveness in the others. This performance is due to the information learned during pretraining and DR- BERT’s ability to use contextual information. 
    more » « less
  2. Measurements are presented of the cross-section for the central exclusive production ofJ/\psi\to\mu^+\mu^- J / ψ μ + μ and\psi(2S)\to\mu^+\mu^- ψ ( 2 S ) μ + μ processes in proton-proton collisions at\sqrt{s} = 13 \ \mathrm{TeV} s = 13 T e V with 2016–2018 data. They are performed by requiring both muons to be in the LHCb acceptance (with pseudorapidity2<\eta_{\mu^±} < 4.5 2 < η μ ± < 4.5 ) and mesons in the rapidity range2.0 < y < 4.5 2.0 < y < 4.5 . The integrated cross-section results are\sigma_{J/\psi\to\mu^+\mu^-}(2.0 σ J / ψ μ + μ ( 2.0 < y J / ψ < 4.5 , 2.0 < η μ ± < 4.5 ) = 400 ± 2 ± 5 ± 12 p b , σ ψ ( 2 S ) μ + μ ( 2.0 < y ψ ( 2 S ) < 4.5 , 2.0 < η μ ± < 4.5 ) = 9.40 ± 0.15 ± 0.13 ± 0.27 p b , where the uncertainties are statistical, systematic and due to the luminosity determination. In addition, a measurement of the ratio of\psi(2S) ψ ( 2 S ) andJ/\psi J / ψ cross-sections, at an average photon-proton centre-of-mass energy of1\ \mathrm{TeV} 1 T e V , is performed, giving$ = 0.1763 ± 0.0029 ± 0.0008 ± 0.0039,$$ where the first uncertainty is statistical, the second systematic and the third due to the knowledge of the involved branching fractions. For the first time, the dependence of theJ/\psi$ J / ψ and\psi(2S) ψ ( 2 S ) cross-sections on the total transverse momentum transfer is determined inpp p p collisions and is found consistent with the behaviour observed in electron-proton collisions. 
    more » « less
    Free, publicly-accessible full text available January 1, 2026