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Viruses are the cause of a considerable burden to human, animal and plant health, whileon the other hand playing an important role in regulating entire ecosystems. The power of newsequencing technologies combined with new tools for processing “Big Data” offers unprecedentedopportunities to answer fundamental questions in virology. Virologists have an urgent need forvirus-specific bioinformatics tools. These developments have led to the formation of the EuropeanVirus Bioinformatics Center, a network of experts in virology and bioinformatics who are joiningforces to enable extensive exchange and collaboration between these research areas. The EVBCstrives to provide talented researchers with a supportive environment free of gender bias, but thegender gap in science, especially in math-intensive fields such as computer science, persists. Tobring more talented women into research and keep them there, we need to highlight role models tospark their interest, and we need to ensure that female scientists are not kept at lower levels but aregiven the opportunity to lead the field. Here we showcase the work of the EVBC and highlight theachievements of some outstanding women experts in virology and viral bioinformatics.

Viruses are the cause of a considerable burden to human, animal and plant health, whileon the other hand playing an important role in regulating entire ecosystems. The power of newsequencing technologies combined with new tools for processing “Big Data” offers unprecedentedopportunities to answer fundamental questions in virology. Virologists have an urgent need forvirus-specific bioinformatics tools. These developments have led to the formation of the EuropeanVirus Bioinformatics Center, a network of experts in virology and bioinformatics who are joiningforces to enable extensive exchange and collaboration between these research areas. The EVBCstrives to provide talented researchers with a supportive environment free of gender bias, but thegender gap in science, especially in math-intensive fields such as computer science, persists. Tobring more talented women into research and keep them there, we need to highlight role models tospark their interest, and we need to ensure that female scientists are not kept at lower levels but aregiven the opportunity to lead the field. Here we showcase the work of the EVBC and highlight theachievements of some outstanding women experts in virology and viral bioinformatics.

Viruses are the cause of a considerable burden to human, animal and plant health, whileon the other hand playing an important role in regulating entire ecosystems. The power of newsequencing technologies combined with new tools for processing “Big Data” offers unprecedentedopportunities to answer fundamental questions in virology. Virologists have an urgent need forvirus-specific bioinformatics tools. These developments have led to the formation of the EuropeanVirus Bioinformatics Center, a network of experts in virology and bioinformatics who are joiningforces to enable extensive exchange and collaboration between these research areas. The EVBCstrives to provide talented researchers with a supportive environment free of gender bias, but thegender gap in science, especially in math-intensive fields such as computer science, persists. Tobring more talented women into research and keep them there, we need to highlight role models tospark their interest, and we need to ensure that female scientists are not kept at lower levels but aregiven the opportunity to lead the field. Here we showcase the work of the EVBC and highlight theachievements of some outstanding women experts in virology and viral bioinformatics.

Viruses are the cause of a considerable burden to human, animal and plant health, whileon the other hand playing an important role in regulating entire ecosystems. The power of newsequencing technologies combined with new tools for processing “Big Data” offers unprecedentedopportunities to answer fundamental questions in virology. Virologists have an urgent need forvirus-specific bioinformatics tools. These developments have led to the formation of the EuropeanVirus Bioinformatics Center, a network of experts in virology and bioinformatics who are joiningforces to enable extensive exchange and collaboration between these research areas. The EVBCstrives to provide talented researchers with a supportive environment free of gender bias, but thegender gap in science, especially in math-intensive fields such as computer science, persists. Tobring more talented women into research and keep them there, we need to highlight role models tospark their interest, and we need to ensure that female scientists are not kept at lower levels but aregiven the opportunity to lead the field. Here we showcase the work of the EVBC and highlight theachievements of some outstanding women experts in virology and viral bioinformatics.

Viruses are the cause of a considerable burden to human, animal and plant health, whileon the other hand playing an important role in regulating entire ecosystems. The power of newsequencing technologies combined with new tools for processing “Big Data” offers unprecedentedopportunities to answer fundamental questions in virology. Virologists have an urgent need forvirus-specific bioinformatics tools. These developments have led to the formation of the EuropeanVirus Bioinformatics Center, a network of experts in virology and bioinformatics who are joiningforces to enable extensive exchange and collaboration between these research areas. The EVBCstrives to provide talented researchers with a supportive environment free of gender bias, but thegender gap in science, especially in math-intensive fields such as computer science, persists. Tobring more talented women into research and keep them there, we need to highlight role models tospark their interest, and we need to ensure that female scientists are not kept at lower levels but aregiven the opportunity to lead the field. Here we showcase the work of the EVBC and highlight theachievements of some outstanding women experts in virology and viral bioinformatics.

Viruses are the cause of a considerable burden to human, animal and plant health, while on the other hand playing an important role in regulating entire ecosystems. The power of new sequencing technologies combined with new tools for processing "Big Data" offers unprecedented opportunities to answer fundamental questions in virology. Virologists have an urgent need for virus-specific bioinformatics tools. These developments have led to the formation of the European Virus Bioinformatics Center, a network of experts in virology and bioinformatics who are joining forces to enable extensive exchange and collaboration between these research areas. The EVBC strives to provide talented researchers with a supportive environment free of gender bias, but the gender gap in science, especially in math-intensive fields such as computer science, persists. To bring more talented women into research and keep them there, we need to highlight role models to spark their interest, and we need to ensure that female scientists are not kept at lower levels but are given the opportunity to lead the field. Here we showcase the work of the EVBC and highlight the achievements of some outstanding women experts in virology and viral bioinformatics.

The need to estimate divergence times in evolutionary histories in the presence of various sources of substitution rate variation has stimulated a rich development of relaxed molecular clock models. Viral evolutionary studies frequently adopt an uncorrelated clock model as a generic relaxed molecular clock process, but this may impose considerable estimation bias if discrete rate variation exists among clades or lineages. For HIV-1 group M, rate variation among subtypes has been shown to result in inconsistencies in time to the most recent common ancestor estimation. Although this calls into question the adequacy of available molecular dating methods, no solution to this problem has been offered so far. Here, we investigate the use of mixed effects molecular clock models, which combine both fixed and random effects in the evolutionary rate, to estimate divergence times. Using simulation, we demonstrate that this model outperforms existing molecular clock models in a Bayesian framework for estimating time-measured phylogenies in the presence of mixed sources of rate variation, while also maintaining good performance in simpler scenarios. By analysing a comprehensive HIV-1 group M complete genome data set we confirm considerable rate variation among subtypes that is not adequately modelled by uncorrelated relaxed clock models. The mixed effects clock model can accommodate this rate variation and results in a time to the most recent common ancestor of HIV-1 group M of 1920 (1915-25), which is only slightly earlier than the uncorrelated relaxed clock estimate for the same data set. The use of complete genome data appears to have a more profound impact than the molecular clock model because it reduces the credible intervals by 50 per cent relative to similar estimates based on short envelope gene sequences.

The need to estimate divergence times in evolutionary histories in the presence of various sources of substitution rate variation has stimulated a rich development of relaxed molecular clock models. Viral evolutionary studies frequently adopt an uncorrelated clock model as a generic relaxed molecular clock process, but this may impose considerable estimation bias if discrete rate variation exists among clades or lineages. For HIV-1 group M, rate variation among subtypes has been shown to result in inconsistencies in time to the most recent common ancestor estimation. Although this calls into question the adequacy of available molecular dating methods, no solution to this problem has been offered so far. Here, we investigate the use of mixed effects molecular clock models, which combine both fixed and random effects in the evolutionary rate, to estimate divergence times. Using simulation, we demonstrate that this model outperforms existing molecular clock models in a Bayesian framework for estimating time-measured phylogenies in the presence of mixed sources of rate variation, while also maintaining good performance in simpler scenarios. By analysing a comprehensive HIV-1 group M complete genome data set we confirm considerable rate variation among subtypes that is not adequately modelled by uncorrelated relaxed clock models. The mixed effects clock model can accommodate this rate variation and results in a time to the most recent common ancestor of HIV-1 group M of 1920 (1915-25), which is only slightly earlier than the uncorrelated relaxed clock estimate for the same data set. The use of complete genome data appears to have a more profound impact than the molecular clock model because it reduces the credible intervals by 50 per cent relative to similar estimates based on short envelope gene sequences.