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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
binding
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publications
talks
Phenonaut; a tool for multiomic data integration, analysis, prediction, and inference
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Data integration workflows for multiparametric phenotypic data take many forms across academia and industry. Efforts with limited resources and smaller teamsoften encountered in academia can easily fall short of data integration best practices for processing and combining high content imaging, proteomics,metabolomics and other omics data. The additional difficulty in applying literature techniques with example code in disparate repositories, languages and compute environments means new techniques require significant investment before use. We present Phenonaut, a Python software package designed to address the data workflow needs of integration, migration, automation, and auditability in the application of literature and proprietary techniques for data source and structure agnostic workflow creation. The application of Phenonaut for omics analysis by non-computational specialists is exemplified by several use cases to demonstrate how the framework can be used for knowledge extraction from diverse biological datasets.
Phenonaut; a tool for multiomic data integration, analysis, prediction, and inference
Published:
Data integration workflows for multiparametric phenotypic data take many forms across academia and industry. Efforts with limited resources and smaller teamsoften encountered in academia can easily fall short of data integration best practices for processing and combining high content imaging, proteomics,metabolomics and other omics data. The additional difficulty in applying literature techniques with example code in disparate repositories, languages and compute environments means new techniques require significant investment before use. We present Phenonaut, a Python software package designed to address the data workflow needs of integration, migration, automation, and auditability in the application of literature and proprietary techniques for data source and structure agnostic workflow creation. The application of Phenonaut for omics analysis by non-computational specialists is exemplified by several use cases to demonstrate how the framework can be used for knowledge extraction from diverse biological datasets.
Talk on simulation of protein ligand binding
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Talk on protein ligand binding at equilibrium
Tutorial on simulation of protein ligand binding using PyBindingCurve
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Tutorial on the application of PyBindingCurve to simulate protein ligand binding at equilibrium.