Measuring Effective Learning in an Epigenetics MOOC
This is an active BioNLP research project. We are investigating the representation, transmission, learning, recall, and reproduction of scientific knowledge via human natural language. We are interested in the neurocognitive structure of human scientific knowledge and its communication through written speech. We are particularly interested in how science can be taught most effectively, and expect that our results will be a contribution to the learning sciences, and the STEM disciplines in particular.
Render 3D Volumes in ImageJ From Single Molecule Point Localization Data
The goal of this team will be to render a point cloud of 3D super-resolution data directly into an ImageJ 3D (XYZ) volume with appropriate image metadata. The project should use core ImageJ framework, such as ImageJ Ops, and should bypass any intermediate steps such as writing the data to a TIFF stack.
The Effect of Institutional Prestige on Academic Collaboration
Explore the roles that institutional prestige plays in shaping academic collaboration in the biosciences by comparing how interdisciplinary research is distributed over prestige rankings.
Creation of a Python Package That Provides Utilities to Summarize RNA-Seq Experiments
The results of RNA-Seq experiments can be difficult to summarize and navigate. Another shortcoming of transcriptomics studies is that machine learning algorithms are underutilized in the literature. The principal goal of this project would be to create a Python package that facilitates the use of machine learning tools (e.g. sklearn) while producing results that are compatible with a downstream visualization tool.
Development of a Suite of Tools to Assemble and Align Long Sequencing Reads
The end product is a suite of tools to assemble and align a long read input file. We are going to develop the alignment-free filtering algorithms based on k-mer counts from scratch. We will then implement string graph algorithms for sequence assembly and NW and SW alignment algorithms.
Creation of Software for Rapid Analysis of Fluorescence Binding Data
The software will collect raw data to determine relevants signals and estimate the parameters of the quadratic binding equation. Using these estimates, fit the equation to the experimental data and plot. https://github.com/Guilz/rfret
A Geospatial Analysis of the Relationship Between Science Education Funding and Policy Outcomes
This team will develop a public web page with interactive data visualizations demonstrating conclusions and allowing visitors to interact with the data in ways that enhance understanding.
Prediction of Brain Age From EEG
Development of an algorithm or analysis software that can evaluate an individual’s brain age based on an EEG dataset.
Mining for eQTLs in the Genomic Data Commons
This project will mine the publicly available cancer genome atlas (TCGA) for gene expression markers of specific tissue types, cancer subtypes and genetic background effects.
A tool that predicts information about Transcription Factors including cell type activity, binding sites, associated eRNAs, regulated genes.
Development of Open Educational Resources for Module-based Learning in the Cloud
The goal of this project will be to develop a dashboard or learning interface that can easily be ported to any openly available cloud resource with support for pluggable education modules designed to teach different topics.
Chemical Precursor and Synthesis Pathway Identification Derived From Publicly Available Data
Develop software to leverage existing and currently underutilized data from publicly available databases and commercially available screening libraries to train a machine learning algorithm to identify chemical precursors and synthesis pathways that will lower the overall cost of manufacture for industrial scale products, pharmaceuticals, and academic lab-generated chemical tools.
Genome Analysis and Visualization With valr
Further develop the speed and utility of the valr R package (http://rnabioco.github.io/valr
). Work on the C++ back-end, develop reproducible analysis workflows using valr and Rmarkdown, or develop new genomic visualzations using valr and Shiny.
Feature Development for PhenVar, a tool for exploring phenotypes associated with genetic mutations
PhenVar, originally developed at the January 2017 NCBI Hackathon, now has a web presence here at BioFrontiers. We’d like to enhance its functionality by adding support for generating phenotypic networks and haploblock associations. (https://phenvar.colorado.edu)