Tyler Kolisnik on Muck Rack

Tyler Kolisnik

Vancouver
As seen in: BMC Cancer
Bioinformatician/Computational Biologist/Data Scientist. Canadian 🇨🇦.
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Articles

pyRforest: A comprehensive R package for genomic data analysis featuring scikit-learn Random Forests in R

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By Tyler Kolisnik, Faeze Keshavarz-Rahaghi, Rachel Purcell, ADAM SMITH
| biorxiv.org
Abstract Random Forest models are widely used in genomic data analysis and can offer insights into complex biological mechanisms, particularly when features influence the target in interactive, non-linear, or non-additive ways. Currently, some of the most efficient Random Forest methods in terms of computational speed are implemented in Python. However, many biologists use R for genomic data analysis, as R offers a unified platform for performing additional statistical analysis and visualization.
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pyRforest: A comprehensive R package for genomic data analysis featuring scikit-learn Random Forests in R

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By Tyler Kolisnik, Rachel Purcell, Adam Smith, Faeze Keshavarz-Rahaghi
| biorxiv.org
Abstract Random Forest models are widely used in genomic data analysis and can offer insights into complex biological mechanisms, particularly where features influence the target in interactive, non-linear, or non-additive ways. Currently, some of the most efficient random forest methods, in terms of computational speed, are implemented in Python.
Open in Who Shared Issue with article?

MetaFunc: Taxonomic and Functional Analyses of High Throughput Sequencing for Microbiomes

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By Tyler Kolisnik, Frank Frizelle, Rachel Purcell, Sebastian Schmeier
| biorxiv.org
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