#epistasis — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #epistasis, aggregated by home.social.
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No Gene Acts Alone
Genes and their variants interact in complex ways, so even “harmful” mutations can sometimes cancel each other out,…
#NewsBeep #News #Science #ASLenzyme #CA #Canada #diseaseriskprediction #doublemutants #epistasis #geneticinteractions #intrageniccomplementation #penetrance #precisiongenomics #proteincomplexes #variantrescue
https://www.newsbeep.com/ca/423212/ -
Popova et al. studied the evolution of M. tuberculosum under drug pressure using a unified phylogeny-based approach to reveal both drug-dependent evolution and epistatic interactions between sites.
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Popova et al. studied the evolution of M. tuberculosum under drug pressure using a unified phylogeny-based approach to reveal both drug-dependent evolution and epistatic interactions between sites.
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Popova et al. studied the evolution of M. tuberculosum under drug pressure using a unified phylogeny-based approach to reveal both drug-dependent evolution and epistatic interactions between sites.
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Popova et al. studied the evolution of M. tuberculosum under drug pressure using a unified phylogeny-based approach to reveal both drug-dependent evolution and epistatic interactions between sites.
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Popova et al. studied the evolution of M. tuberculosum under drug pressure using a unified phylogeny-based approach to reveal both drug-dependent evolution and epistatic interactions between sites.
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Integrated in vivo combinatorial functional genomics and spatial transcriptomics of tumours to decode genotype-to-phenotype relationships
Animal experiments Group size was determined on the basis of our experience in previous experiments68,69. For HDTV injections,…
#NewsBeep #News #Genetics #BiomedicalEngineering/Biotechnology #Biomedicine #Cancermodels #Epistasis #general #Science #Tumourheterogeneity #UK #UnitedKingdom
https://www.newsbeep.com/uk/30793/ -
Structural and molecular #basis of the #epistasis effect in enhanced affinity between #SARS-CoV-2 #KP3 and #ACE2 http://biorxiv.org/cgi/content/short/2024.09.03.610799v1?rss=1
KP.3, featuring F456L and Q493E, exhibits a markedly enhanced ACE2 binding affinity compared to #KP2 and #JN1 #variant due to synergistic effects between these mutations.
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Structural and molecular #basis of the #epistasis effect in enhanced affinity between #SARS-CoV-2 #KP3 and #ACE2 http://biorxiv.org/cgi/content/short/2024.09.03.610799v1?rss=1
KP.3, featuring F456L and Q493E, exhibits a markedly enhanced ACE2 binding affinity compared to #KP2 and #JN1 #variant due to synergistic effects between these mutations.
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Structural and molecular #basis of the #epistasis effect in enhanced affinity between #SARS-CoV-2 #KP3 and #ACE2 http://biorxiv.org/cgi/content/short/2024.09.03.610799v1?rss=1
KP.3, featuring F456L and Q493E, exhibits a markedly enhanced ACE2 binding affinity compared to #KP2 and #JN1 #variant due to synergistic effects between these mutations.
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Structural and molecular #basis of the #epistasis effect in enhanced affinity between #SARS-CoV-2 #KP3 and #ACE2 http://biorxiv.org/cgi/content/short/2024.09.03.610799v1?rss=1
KP.3, featuring F456L and Q493E, exhibits a markedly enhanced ACE2 binding affinity compared to #KP2 and #JN1 #variant due to synergistic effects between these mutations.
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Structural and molecular #basis of the #epistasis effect in enhanced affinity between #SARS-CoV-2 #KP3 and #ACE2 http://biorxiv.org/cgi/content/short/2024.09.03.610799v1?rss=1
KP.3, featuring F456L and Q493E, exhibits a markedly enhanced ACE2 binding affinity compared to #KP2 and #JN1 #variant due to synergistic effects between these mutations.
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#Epistasis mediates the evolution of #receptor binding mode in recent #human #H3N2 #hemagglutinin, Nat Commun.: https://www.nature.com/articles/s41467-024-49487-4
Combinatorial #mutagenesis reveals that G186D and D190N, along with other natural mutations in recent H3N2 strains, alter compatibility with a common egg-adaptive mutation in seasonal influenza vaccines. Our findings elucidate role of epistasis in shaping recent evolution of human hemagglutinin & substantiate high evolvability of its receptor-binding mode.
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#Epistasis mediates the evolution of #receptor binding mode in recent #human #H3N2 #hemagglutinin, Nat Commun.: https://www.nature.com/articles/s41467-024-49487-4
Combinatorial #mutagenesis reveals that G186D and D190N, along with other natural mutations in recent H3N2 strains, alter compatibility with a common egg-adaptive mutation in seasonal influenza vaccines. Our findings elucidate role of epistasis in shaping recent evolution of human hemagglutinin & substantiate high evolvability of its receptor-binding mode.
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#Epistasis mediates the evolution of #receptor binding mode in recent #human #H3N2 #hemagglutinin, Nat Commun.: https://www.nature.com/articles/s41467-024-49487-4
Combinatorial #mutagenesis reveals that G186D and D190N, along with other natural mutations in recent H3N2 strains, alter compatibility with a common egg-adaptive mutation in seasonal influenza vaccines. Our findings elucidate role of epistasis in shaping recent evolution of human hemagglutinin & substantiate high evolvability of its receptor-binding mode.
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#Epistasis mediates the evolution of #receptor binding mode in recent #human #H3N2 #hemagglutinin, Nat Commun.: https://www.nature.com/articles/s41467-024-49487-4
Combinatorial #mutagenesis reveals that G186D and D190N, along with other natural mutations in recent H3N2 strains, alter compatibility with a common egg-adaptive mutation in seasonal influenza vaccines. Our findings elucidate role of epistasis in shaping recent evolution of human hemagglutinin & substantiate high evolvability of its receptor-binding mode.
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#Epistasis mediates the evolution of #receptor binding mode in recent #human #H3N2 #hemagglutinin, Nat Commun.: https://www.nature.com/articles/s41467-024-49487-4
Combinatorial #mutagenesis reveals that G186D and D190N, along with other natural mutations in recent H3N2 strains, alter compatibility with a common egg-adaptive mutation in seasonal influenza vaccines. Our findings elucidate role of epistasis in shaping recent evolution of human hemagglutinin & substantiate high evolvability of its receptor-binding mode.
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#Epistasis lowers the #genetic #barrier to #SARS-CoV-2 neutralizing #antibody #escape https://www.nature.com/articles/s41467-023-35927-0
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The first descriptor is the mean Hamming distance of the training MSA data to the mutated sequence (D in the figure). This quantifies the "quality" of the data for the given problem - the closer to the mutated sequence, the better.
We show the Hamming distance is connected to the statistical #bias of the inferred model, with a prefactor (J0) that depends by the amount of high-order #epistasis that is not explicitly accounted for by the model.
(in the figure: B = number of sequences)
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The first descriptor is the mean Hamming distance of the training MSA data to the mutated sequence (D in the figure). This quantifies the "quality" of the data for the given problem - the closer to the mutated sequence, the better.
We show the Hamming distance is connected to the statistical #bias of the inferred model, with a prefactor (J0) that depends by the amount of high-order #epistasis that is not explicitly accounted for by the model.
(in the figure: B = number of sequences)
-
The first descriptor is the mean Hamming distance of the training MSA data to the mutated sequence (D in the figure). This quantifies the "quality" of the data for the given problem - the closer to the mutated sequence, the better.
We show the Hamming distance is connected to the statistical #bias of the inferred model, with a prefactor (J0) that depends by the amount of high-order #epistasis that is not explicitly accounted for by the model.
(in the figure: B = number of sequences)
-
The first descriptor is the mean Hamming distance of the training MSA data to the mutated sequence (D in the figure). This quantifies the "quality" of the data for the given problem - the closer to the mutated sequence, the better.
We show the Hamming distance is connected to the statistical #bias of the inferred model, with a prefactor (J0) that depends by the amount of high-order #epistasis that is not explicitly accounted for by the model.
(in the figure: B = number of sequences)
-
The first descriptor is the mean Hamming distance of the training MSA data to the mutated sequence (D in the figure). This quantifies the "quality" of the data for the given problem - the closer to the mutated sequence, the better.
We show the Hamming distance is connected to the statistical #bias of the inferred model, with a prefactor (J0) that depends by the amount of high-order #epistasis that is not explicitly accounted for by the model.
(in the figure: B = number of sequences)
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New paper with @CCWendling Co-transfer of functionally interdependent genes contributes to genome mosaicism in lambdoid phages - we use an approach that does not rely on the core genome phylogeny to infer gene transfers, and then detect co-transferred genes in lambdoid phages, we highlight known and novel co-transfer examples
#phage #evolution #recombination #HGT #Epistasis
https://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000915 -
New paper with @CCWendling Co-transfer of functionally interdependent genes contributes to genome mosaicism in lambdoid phages - we use an approach that does not rely on the core genome phylogeny to infer gene transfers, and then detect co-transferred genes in lambdoid phages, we highlight known and novel co-transfer examples
#phage #evolution #recombination #HGT #Epistasis
https://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000915 -
New paper with @CCWendling Co-transfer of functionally interdependent genes contributes to genome mosaicism in lambdoid phages - we use an approach that does not rely on the core genome phylogeny to infer gene transfers, and then detect co-transferred genes in lambdoid phages, we highlight known and novel co-transfer examples
#phage #evolution #recombination #HGT #Epistasis
https://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000915 -
#introduction I mostly work using in silico experiments and mathematical modeling to understand how properties of biological systems affect their evolution. Some of the topics I have studied include:
The effect of #epistasis in the accumulation and purging of deleterious mutations in organisms with high mutation rates. #mutationload
How the #modularity of
#DevelopmentalProcesses affect the #PhenotypicVariability of biological systems. #IntroductionBias -
#introduction I mostly work using in silico experiments and mathematical modeling to understand how properties of biological systems affect their evolution. Some of the topics I have studied include:
The effect of #epistasis in the accumulation and purging of deleterious mutations in organisms with high mutation rates. #mutationload
How the #modularity of
#DevelopmentalProcesses affect the #PhenotypicVariability of biological systems. #IntroductionBias
