Project Proposals for April 2018 NCBI-UCSC-NorCal Bioinformatics Hackathon
Proposals for Bioinformatics Tools or Pipelines that will be built at the April (2-4) Hackathon. Please note, these tools should be broadly applicable to at least a part of the bioinformatics community, and having a team lead dramatically increases the probability that the project will be a go.
In ~ two sentences, please tell us about the project you are proposing!
Why is this applicable to others in the community?
Do you have a team lead for this project
A team leader is responsible for proposing a project for the event and having a clear vision for developing a solution. To accomplish their goal team leader is responsible for leading their team of 5-6 individuals at the event - this means clearly defining and delegating tasks, incorporating team members’ ideas to accomplish the goal at stake, and ensuring success of the team.
If so, who is that person, and what is their email address?
+ Identify phages and viruses from metagenomes
+ Classify SRA datasets by source
+ Identify QTLs in plants
+ Use machine learning to characterize viral sequences
+ Develop a Machine Learning Tool to Differentiate Between Synthetic and Natural Genomic Regions in Plants.
+ Compute human ancestral alleles from chimp, gorillas, orangutan and macaque; and provide API access to ancestral allele for a given position on human genome GRCh38.
+ Machine learning pipelines for germline rare variants linked to phenotypes
+ Building an interactive online environment to run NCBI-style hackathons
+ An integrated pipeline for novel virus discovery
+ Probabalistic identification of past viral exposure based on non-native sequences in host genome
+ Packaging and distributing an automatic corpus-updater for NLP tools
+ Phenotypic Indexing of (crispr derived) mouse models
+ Expanding and publicizing a Shiny app for visualizing protein correlation profiling data,
+ Building a pipeline for efficient partitioning of barcodes,
+ Creating a public JBrowse database for all Staphylococcus aureus genomes,
+ Simulating tumor genomes,
+ Associating somatic mutations with clinical outcomes,
+ Simplifying access to shared-data repositories from python, and
+ Building a pipeline for searching for virus-associated protein domains in NGS datasets.
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