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#compbio — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #compbio, aggregated by home.social.

  1. Pinto et al. present SCINKD as a framework to identify unannotated sex chromosomes and curate diploid genome assemblies from a single individual.

    🔗 doi.org/10.1093/molbev/msag067

    #evobio #molbio #compbio

  2. Pinto et al. present SCINKD as a framework to identify unannotated sex chromosomes and curate diploid genome assemblies from a single individual.

    🔗 doi.org/10.1093/molbev/msag067

    #evobio #molbio #compbio

  3. Pinto et al. present SCINKD as a framework to identify unannotated sex chromosomes and curate diploid genome assemblies from a single individual.

    🔗 doi.org/10.1093/molbev/msag067

    #evobio #molbio #compbio

  4. Pinto et al. present SCINKD as a framework to identify unannotated sex chromosomes and curate diploid genome assemblies from a single individual.

    🔗 doi.org/10.1093/molbev/msag067

    #evobio #molbio #compbio

  5. Pinto et al. present SCINKD as a framework to identify unannotated sex chromosomes and curate diploid genome assemblies from a single individual.

    🔗 doi.org/10.1093/molbev/msag067

    #evobio #molbio #compbio

  6. Didelot et al. present the R package DiagnoDating for diagnosing issues in a reconstructed dated phylogeny, including outlier detection, posterior predictive checking and residual analysis.

    🔗 doi.org/10.1093/molbev/msag093

    #evobio #molbio #compbio #phylogeny

  7. Didelot et al. present the R package DiagnoDating for diagnosing issues in a reconstructed dated phylogeny, including outlier detection, posterior predictive checking and residual analysis.

    🔗 doi.org/10.1093/molbev/msag093

    #evobio #molbio #compbio #phylogeny

  8. Didelot et al. present the R package DiagnoDating for diagnosing issues in a reconstructed dated phylogeny, including outlier detection, posterior predictive checking and residual analysis.

    🔗 doi.org/10.1093/molbev/msag093

    #evobio #molbio #compbio #phylogeny

  9. Didelot et al. present the R package DiagnoDating for diagnosing issues in a reconstructed dated phylogeny, including outlier detection, posterior predictive checking and residual analysis.

    🔗 doi.org/10.1093/molbev/msag093

    #evobio #molbio #compbio #phylogeny

  10. Didelot et al. present the R package DiagnoDating for diagnosing issues in a reconstructed dated phylogeny, including outlier detection, posterior predictive checking and residual analysis.

    🔗 doi.org/10.1093/molbev/msag093

    #evobio #molbio #compbio #phylogeny

  11. Daniel Huson introduces displacement-optimized tanglegrams (DO-tanglegrams), a new approach that applies equally to trees and rooted phylogenetic networks, performing better than cophylo on trees and then NN-tanglegram on networks.

    🔗 doi.org/10.1093/molbev/msag066

    #evobio #molbio #compbio

  12. Daniel Huson introduces displacement-optimized tanglegrams (DO-tanglegrams), a new approach that applies equally to trees and rooted phylogenetic networks, performing better than cophylo on trees and then NN-tanglegram on networks.

    🔗 doi.org/10.1093/molbev/msag066

    #evobio #molbio #compbio

  13. Daniel Huson introduces displacement-optimized tanglegrams (DO-tanglegrams), a new approach that applies equally to trees and rooted phylogenetic networks, performing better than cophylo on trees and then NN-tanglegram on networks.

    🔗 doi.org/10.1093/molbev/msag066

    #evobio #molbio #compbio

  14. Daniel Huson introduces displacement-optimized tanglegrams (DO-tanglegrams), a new approach that applies equally to trees and rooted phylogenetic networks, performing better than cophylo on trees and then NN-tanglegram on networks.

    🔗 doi.org/10.1093/molbev/msag066

    #evobio #molbio #compbio

  15. Daniel Huson introduces displacement-optimized tanglegrams (DO-tanglegrams), a new approach that applies equally to trees and rooted phylogenetic networks, performing better than cophylo on trees and then NN-tanglegram on networks.

    🔗 doi.org/10.1093/molbev/msag066

    #evobio #molbio #compbio

  16. McArthur et al. present piqtree, an easy to use, open-source Python package that provides Python script-based control of IQ-TREE’s phylogenetic inference engine.

    🔗 doi.org/10.1093/molbev/msag061

    #evobio #molbio #compbio

  17. McArthur et al. present piqtree, an easy to use, open-source Python package that provides Python script-based control of IQ-TREE’s phylogenetic inference engine.

    🔗 doi.org/10.1093/molbev/msag061

    #evobio #molbio #compbio

  18. McArthur et al. present piqtree, an easy to use, open-source Python package that provides Python script-based control of IQ-TREE’s phylogenetic inference engine.

    🔗 doi.org/10.1093/molbev/msag061

    #evobio #molbio #compbio

  19. McArthur et al. present piqtree, an easy to use, open-source Python package that provides Python script-based control of IQ-TREE’s phylogenetic inference engine.

    🔗 doi.org/10.1093/molbev/msag061

    #evobio #molbio #compbio

  20. McArthur et al. present piqtree, an easy to use, open-source Python package that provides Python script-based control of IQ-TREE’s phylogenetic inference engine.

    🔗 doi.org/10.1093/molbev/msag061

    #evobio #molbio #compbio

  21. @sishuowang & Meade introduce phyloHessian to enable the use of complex mixture substitution models in molecular dating. Empirical analysis of ancient symbiont lineages leads to a revised understanding of their host association origins.

    🔗 doi.org/10.1093/molbev/msag039

    #evobio #molbio #compbio

  22. @sishuowang & Meade introduce phyloHessian to enable the use of complex mixture substitution models in molecular dating. Empirical analysis of ancient symbiont lineages leads to a revised understanding of their host association origins.

    🔗 doi.org/10.1093/molbev/msag039

    #evobio #molbio #compbio

  23. @sishuowang & Meade introduce phyloHessian to enable the use of complex mixture substitution models in molecular dating. Empirical analysis of ancient symbiont lineages leads to a revised understanding of their host association origins.

    🔗 doi.org/10.1093/molbev/msag039

    #evobio #molbio #compbio

  24. @sishuowang & Meade introduce phyloHessian to enable the use of complex mixture substitution models in molecular dating. Empirical analysis of ancient symbiont lineages leads to a revised understanding of their host association origins.

    🔗 doi.org/10.1093/molbev/msag039

    #evobio #molbio #compbio

  25. @sishuowang & Meade introduce phyloHessian to enable the use of complex mixture substitution models in molecular dating. Empirical analysis of ancient symbiont lineages leads to a revised understanding of their host association origins.

    🔗 doi.org/10.1093/molbev/msag039

    #evobio #molbio #compbio

  26. Robbins, Liu & Kelly present RECUR, a method for identifying recurrent amino acid substitutions from multiple sequence alignments that is fast, easy to use, and scalable to thousands of sequences.

    🔗 doi.org/10.1093/molbev/msag036

    #evobio #molbio #compbio

  27. Robbins, Liu & Kelly present RECUR, a method for identifying recurrent amino acid substitutions from multiple sequence alignments that is fast, easy to use, and scalable to thousands of sequences.

    🔗 doi.org/10.1093/molbev/msag036

    #evobio #molbio #compbio

  28. Robbins, Liu & Kelly present RECUR, a method for identifying recurrent amino acid substitutions from multiple sequence alignments that is fast, easy to use, and scalable to thousands of sequences.

    🔗 doi.org/10.1093/molbev/msag036

    #evobio #molbio #compbio

  29. Robbins, Liu & Kelly present RECUR, a method for identifying recurrent amino acid substitutions from multiple sequence alignments that is fast, easy to use, and scalable to thousands of sequences.

    🔗 doi.org/10.1093/molbev/msag036

    #evobio #molbio #compbio

  30. Robbins, Liu & Kelly present RECUR, a method for identifying recurrent amino acid substitutions from multiple sequence alignments that is fast, easy to use, and scalable to thousands of sequences.

    🔗 doi.org/10.1093/molbev/msag036

    #evobio #molbio #compbio

  31. Deng et al. present TreeProfiler, a tool for automated annotation and interactive exploration of hundreds of features along large gene and species trees, with seamless summarization of mapped traits at internal nodes.

    🔗 doi.org/10.1093/molbev/msag028

    #evobio #molbio #compbio

  32. Deng et al. present TreeProfiler, a tool for automated annotation and interactive exploration of hundreds of features along large gene and species trees, with seamless summarization of mapped traits at internal nodes.

    🔗 doi.org/10.1093/molbev/msag028

    #evobio #molbio #compbio

  33. Deng et al. present TreeProfiler, a tool for automated annotation and interactive exploration of hundreds of features along large gene and species trees, with seamless summarization of mapped traits at internal nodes.

    🔗 doi.org/10.1093/molbev/msag028

    #evobio #molbio #compbio

  34. Deng et al. present TreeProfiler, a tool for automated annotation and interactive exploration of hundreds of features along large gene and species trees, with seamless summarization of mapped traits at internal nodes.

    🔗 doi.org/10.1093/molbev/msag028

    #evobio #molbio #compbio

  35. Martí-Gómez et al. developed gpmap-tools, integrating models for inference, phenotypic imputation, and error estimation from multiplex assays of variant effect data or natural sequences in the presence of genetic interactions.

    🔗 doi.org/10.1093/molbev/msag023

    #evobio #molbio #compbio

  36. Martí-Gómez et al. developed gpmap-tools, integrating models for inference, phenotypic imputation, and error estimation from multiplex assays of variant effect data or natural sequences in the presence of genetic interactions.

    🔗 doi.org/10.1093/molbev/msag023

    #evobio #molbio #compbio

  37. Martí-Gómez et al. developed gpmap-tools, integrating models for inference, phenotypic imputation, and error estimation from multiplex assays of variant effect data or natural sequences in the presence of genetic interactions.

    🔗 doi.org/10.1093/molbev/msag023

    #evobio #molbio #compbio

  38. Martí-Gómez et al. developed gpmap-tools, integrating models for inference, phenotypic imputation, and error estimation from multiplex assays of variant effect data or natural sequences in the presence of genetic interactions.

    🔗 doi.org/10.1093/molbev/msag023

    #evobio #molbio #compbio

  39. Martí-Gómez et al. developed gpmap-tools, integrating models for inference, phenotypic imputation, and error estimation from multiplex assays of variant effect data or natural sequences in the presence of genetic interactions.

    🔗 doi.org/10.1093/molbev/msag023

    #evobio #molbio #compbio

  40. Anchieri et al. benchmark the inference of selection with aDNA-like time series datasets, showing that ApproxWF can accurately estimate selection with datasets of ∼100 individuals when selection is strong.

    🔗 doi.org/10.1093/gbe/evaf234

    #genome #evolution #compbio

  41. Anchieri et al. benchmark the inference of selection with aDNA-like time series datasets, showing that ApproxWF can accurately estimate selection with datasets of ∼100 individuals when selection is strong.

    🔗 doi.org/10.1093/gbe/evaf234

    #genome #evolution #compbio

  42. Anchieri et al. benchmark the inference of selection with aDNA-like time series datasets, showing that ApproxWF can accurately estimate selection with datasets of ∼100 individuals when selection is strong.

    🔗 doi.org/10.1093/gbe/evaf234

    #genome #evolution #compbio

  43. Anchieri et al. benchmark the inference of selection with aDNA-like time series datasets, showing that ApproxWF can accurately estimate selection with datasets of ∼100 individuals when selection is strong.

    🔗 doi.org/10.1093/gbe/evaf234

    #genome #evolution #compbio

  44. Anchieri et al. benchmark the inference of selection with aDNA-like time series datasets, showing that ApproxWF can accurately estimate selection with datasets of ∼100 individuals when selection is strong.

    🔗 doi.org/10.1093/gbe/evaf234

    #genome #evolution #compbio

  45. Ramos-González et al. present PharaohFUN, a web application designed for the evolutionary and functional analysis of protein sequences in photosynthetic eukaryotes, leveraging orthology relationships.

    🔗 doi.org/10.1093/molbev/msag011

    #evobio #molbio #compbio

  46. Ramos-González et al. present PharaohFUN, a web application designed for the evolutionary and functional analysis of protein sequences in photosynthetic eukaryotes, leveraging orthology relationships.

    🔗 doi.org/10.1093/molbev/msag011

    #evobio #molbio #compbio

  47. Ramos-González et al. present PharaohFUN, a web application designed for the evolutionary and functional analysis of protein sequences in photosynthetic eukaryotes, leveraging orthology relationships.

    🔗 doi.org/10.1093/molbev/msag011

    #evobio #molbio #compbio

  48. Ramos-González et al. present PharaohFUN, a web application designed for the evolutionary and functional analysis of protein sequences in photosynthetic eukaryotes, leveraging orthology relationships.

    🔗 doi.org/10.1093/molbev/msag011

    #evobio #molbio #compbio

  49. Ramos-González et al. present PharaohFUN, a web application designed for the evolutionary and functional analysis of protein sequences in photosynthetic eukaryotes, leveraging orthology relationships.

    🔗 doi.org/10.1093/molbev/msag011

    #evobio #molbio #compbio

  50. Malik et al. present the web-based Structome-AlignViewer, for evaluating structure-aware alignments through spatial mapping of alignment columns to protein structures, and quantitative confidence scoring.

    🔗 doi.org/10.1093/gbe/evag004

    #genome #evolution #compbio