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Using phylodynamics and decision trees to estimate the effects of mutation on viral fitness

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Kein Logo verfügbarBanff International Research Station (BIRS) for Mathematical Innovation and Discovery
 Kepler, Lenora

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Using phylodynamics and decision trees to estimate the effects of mutation on viral fitness
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Anzahl der Teile
38
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Inhaltliche Metadaten

Fachgebiet
Genre
Mathematics and Statistics of Genomic Epidemiology5 / 38
1
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Bayesian community modelling of the microbiome
2
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05:12
Combining sequencing technologies and data mining to study (mega)plasmid families
3
Vorschaubild
05:26
Considerations for estimating Rt in Alberta, Canada
4
Vorschaubild
04:59
Inference of Multiscale Selection using a Continuous Type Birth Death Model
5
Vorschaubild
03:29
Using phylodynamics and decision trees to estimate the effects of mutation on viral fitness
6
Vorschaubild
05:42
Case fatality imputation using machine learning
7
Vorschaubild
03:45
Benchmarking computational doublet-detection methods for single-cell RNA sequencing data
8
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20:12
SARS-CoV-2 Phylodynamic inference - with and without phylogenies
9
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05:50
Do machine learning predictors of microbial phenotype from genotype identify causal variants
10
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04:21
PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data
11
Vorschaubild
04:59
Pop-PUNK-web: In-browser genome sketching for secure real-time genomic epidemiology
12
Vorschaubild
19:53
The evolution of multi-strain bacterial populations
13
Vorschaubild
03:19
ggCaller: a gene caller for bacterial pangenome graphs
14
Vorschaubild
04:28
Deep clustering of bacterial tree images
15
Vorschaubild
15:11
Mapping the shared evolutionary trajectories of resistance genes and other (possibly!) bad actors
16
Vorschaubild
19:16
How different is the flu you transmit from the flu you received
17
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20:12
High-resolution characterization of global Salmonella subpopulations
18
Vorschaubild
21:22
Genomic tracking of SARS-CoV-2 evolution and spread
19
Vorschaubild
19:57
Decomposing the sources of SARS-CoV-2 fitness variation using phylodynamics
20
Vorschaubild
19:54
Genomic epidemiology of SARS-CoV-2 in Quebec
21
Vorschaubild
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Large-scale phylogeography of hCoV-19
22
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20:03
Estimating the age groups that sustain resurging COVID-19 epidemics in the United States
23
Vorschaubild
20:21
Phylodynamics and genealogy-valued Markov processes
24
Vorschaubild
22:23
Bayesian inference of parameters in transmission models
25
Vorschaubild
19:37
Additive uncorrelated relaxed clock models
26
Vorschaubild
22:03
Bayesian modeling and data integration in infectious disease phylodynamics
27
Vorschaubild
22:05
Hierarchical population genomic structure of bacterial pathogens in EnteroBase
28
Vorschaubild
20:25
Estimating population-level HIV transmission dynamics from deep-sequence data
29
Vorschaubild
20:40
Phylogenetic inference with distribution continuum
30
Vorschaubild
24:29
Improving the interpretability of k-mer-based signatures for antibiotic resistance prediction
31
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22:04
Hardware-accelerated genome sketching enables real-time genomic epidemiology of pathogens
32
Vorschaubild
22:40
mbImpute: an accurate and robust imputation method for microbiome data
33
Vorschaubild
21:34
Adaptation to the cervical environment is associated with increased antibiotic susceptibility in Neisseria gonorrhoeae
34
Vorschaubild
17:48
Population genomics of A. baumannii reveals a licentious and highly mobile resistome
35
Vorschaubild
19:28
Increased power from conditional bacterial genome-wide association identifies macrolide resistance mutations in Neisseria gonorrhoeae
36
Vorschaubild
18:11
Synthetic biology approaches to suppression of antibiotic resistance
37
Vorschaubild
19:39
Identifying prognostic pairwise relationships among bacterial species in microbiome studies
38
Vorschaubild
21:25
Interpretable machine learning methods for predicting drug resistance