All-atom 3D structure prediction of transmembrane β-barrel proteins from sequences

56 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Modeling aspects of the language of life through transfer-learning protein sequences (2019, background): “Ar-guably, the most important breakthrough for protein structure prediction over the last decade was a more efficient way of using evolutionary couplings [28 – 31].”
Protein Structure Determination using Metagenome sequence data (2017, neutral): “for sep_x (0,1,2) for sep_y (1,2,4, 8,16,32) ini_mtx = initialize_matrix (sep_x , sep_y) for gap_e (-0.”
Prediction of interresidue contacts with DeepMetaPSICOV in CASP13 (2019, methodology): “During development, the effectiveness of the model was assessed on a variety of data sets including the CASP11 and CASP12 freemodeling (FM) domains, the PSICOV150 set,(8) and membrane proteins fromNugent and Jones(22) andHayat et al.(23)”
Accurate contact predictions for thousands of protein families using PconsC3 (2016, unknown): “This has enabled accurate blind predictions of the structure of soluble proteins [3–5], membrane proteins [6–8], and protein complexes [9, 10].”