Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1.
about
CoeViz: a web-based tool for coevolution analysis of protein residues.Benchmarking Inverse Statistical Approaches for Protein Structure and Design with Exactly Solvable Models.Detection and sequence/structure mapping of biophysical constraints to protein variation in saturated mutational libraries and protein sequence alignments with a dedicated serverPotts Hamiltonian models of protein co-variation, free energy landscapes, and evolutionary fitness.Improving landscape inference by integrating heterogeneous data in the inverse Ising problem.Inference of Epistatic Effects Leading to Entrenchment and Drug Resistance in HIV-1 Protease.ACE: adaptive cluster expansion for maximum entropy graphical model inference.Maximum-Entropy Models of Sequenced Immune Repertoires Predict Antigen-Antibody Affinity.Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis.Inferring repeat-protein energetics from evolutionary information.Inferring interaction partners from protein sequences.Connecting the Sequence-Space of Bacterial Signaling Proteins to Phenotypes Using Coevolutionary Landscapes.Identification of positive selection in genes is greatly improved by using experimentally informed site-specific models.Epistasis in protein evolution.Large-scale identification of coevolution signals across homo-oligomeric protein interfaces by direct coupling analysis.Random versus maximum entropy models of neural population activity.Mutation effects predicted from sequence co-variation.A Quantitative Model to Estimate Drug Resistance in Pathogens.Co-evolution techniques are reshaping the way we do structural bioinformatics.Mutator genomes decay, despite sustained fitness gains, in a long-term experiment with bacteria.Fitness landscape of the human immunodeficiency virus envelope protein that is targeted by antibodies.Coevolutionary Landscape of Kinase Family Proteins: Sequence Probabilities and Functional Motifs.Patterns of coevolving amino acids unveil structural and dynamical domains.Exploring protein sequence-function landscapes.Biomolecular coevolution and its applications: Going from structure prediction toward signaling, epistasis, and function.How Many Protein Sequences Fold to a Given Structure? A Coevolutionary Analysis.Evolving Bacterial Fitness with an Expanded Genetic Code.Optimal Design of Experiments by Combining Coarse and Fine Measurements.Population-specific design of de-immunized protein biotherapeutics.Global pairwise RNA interaction landscapes reveal core features of protein recognition.Coevolution-based inference of amino acid interactions underlying protein functionDesigning bacterial signaling interactions with coevolutionary landscapes
P2860
Q30385417-A4A8DC66-7FD2-4FA0-905D-4D398FE3AE23Q30388077-BFEFCDC5-36B9-4D45-A470-92D5AEE1A709Q30389475-FA6C2647-FF65-4540-998F-8ED5317694DFQ30395457-3D57C331-C11C-4F65-B1D4-EB938E9DEBE9Q31144691-B6E705CA-F5E1-41FE-8B7C-70F949BCB8D6Q33698683-4A2E51ED-C1B9-49A9-AB6E-4B1F3ED73B3DQ34531572-F50970D0-A517-4AA7-8056-26E2DCB2079BQ35988588-87B1A240-747C-4E1A-878D-1070A323D7AFQ36282693-382982B4-7F8D-4924-884D-70CD3AA23C30Q36406261-1FE020AF-749F-4847-A934-AB1217E90FD6Q37379905-F66C6649-4204-47FD-90DE-F914181B1DCAQ37400436-EDE05BD9-A8E9-4047-A2C5-47D88CFB77E6Q37589347-9E9F57D0-8908-432E-B2AE-295BB56FB747Q38718935-48372F79-3B89-4384-93DB-1983F9D1C72DQ38746410-884FCC78-CF3C-4A05-B7DA-3BB4F1212EE5Q38785558-B8D29D35-FF39-441D-9101-AB391D3BDE61Q39018179-FCF9D756-3235-418D-9C9F-1FD2E8C0638FQ39064618-315653C8-E9D0-47DF-AD36-5B7594D34FB1Q41150914-346307A5-92B2-4DC0-ADC6-B1DA39518038Q46274173-A4D55BD3-39FA-4CB7-9826-E888A324B895Q47193141-2A850F3F-BB41-4426-987D-7B9669B16D53Q47213672-D6CDAC78-2EBC-4F8E-A831-00BC866926C6Q47354955-B399A1FB-6151-4947-9587-633BE9CD8025Q47566687-5E38ADF2-77EB-4E33-85FF-35A0D8A3C7F0Q47621840-E6B20917-7D3F-4D63-B0E9-62A61B8E23D9Q47632806-80FD76D5-AC17-4103-AA66-3CE4314D23CEQ49831017-12F9811D-489F-4B29-B35D-F41740597B2DQ50013783-5EC4A380-0077-4E56-A97A-C833DF876185Q50421163-AF464FE7-9555-4487-A62F-F40C03110A48Q55397375-42DAE70E-DA48-418D-A65D-B1069E4708E2Q56532677-208A48B6-D830-4FB0-8461-A1F1DEDFE8BFQ58765695-E98CBE09-BBE2-4A53-9499-00B9302D3501
P2860
Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1.
description
2015 nî lūn-bûn
@nan
2015 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2015 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2015年の論文
@ja
2015年論文
@yue
2015年論文
@zh-hant
2015年論文
@zh-hk
2015年論文
@zh-mo
2015年論文
@zh-tw
2015年论文
@wuu
name
Coevolutionary Landscape Infer ...... tions in Beta-Lactamase TEM-1.
@ast
Coevolutionary Landscape Infer ...... tions in Beta-Lactamase TEM-1.
@en
Coevolutionary Landscape Infer ...... tions in Beta-Lactamase TEM-1.
@nl
type
label
Coevolutionary Landscape Infer ...... tions in Beta-Lactamase TEM-1.
@ast
Coevolutionary Landscape Infer ...... tions in Beta-Lactamase TEM-1.
@en
Coevolutionary Landscape Infer ...... tions in Beta-Lactamase TEM-1.
@nl
prefLabel
Coevolutionary Landscape Infer ...... tions in Beta-Lactamase TEM-1.
@ast
Coevolutionary Landscape Infer ...... tions in Beta-Lactamase TEM-1.
@en
Coevolutionary Landscape Infer ...... tions in Beta-Lactamase TEM-1.
@nl
P2093
P2860
P356
P1476
Coevolutionary Landscape Infer ...... tions in Beta-Lactamase TEM-1.
@en
P2093
Alexander Schug
Hervé Jacquier
Matteo Figliuzzi
P2860
P304
P356
10.1093/MOLBEV/MSV211
P577
2015-10-06T00:00:00Z
P5875
P698
P818
1510.03224