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Dakota Hawkins's Projects

ai icon ai

Work for CS640 at Boston University

awesome-single-cell icon awesome-single-cell

List of software packages for single-cell data analysis, including RNA-seq, ATAC-seq, etc.

datastructure icon datastructure

A few examples in Java from my data structures class at Westminster College.

flex icon flex

A responsive, flexible, Jekyll theme based on The Development's first design.

gnn_penn icon gnn_penn

Repo for becoming familiar with graphical neural networkshttps://gnn.seas.upenn.edu/lectures/lecture-1/

intensipy icon intensipy

Normalize intensity values in 3D image stacks

lapreprint icon lapreprint

📝 A nicely formatted LaTeX preprint template

leidenalg icon leidenalg

Implementation of the Leiden algorithm for various quality functions to be used with igraph in Python.

littleballoffur icon littleballoffur

Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)

lm_filter_bank_python_code icon lm_filter_bank_python_code

Python code for generating Leung-Malik (LM) filter bank that is typically used in texture analysis and classification.

louvain-igraph icon louvain-igraph

Implementation of the Louvain algorithm for community detection with various methods for use with igraph in python.

mathbio icon mathbio

Code from my Mathematical Biology class at the University of Utah. Files are numerical solutions to applied PDE models in biology.

mcm2015 icon mcm2015

Code used during the 2015 Mathematical Competition in Modeling. The code models the spread of ebola through a regional network that accounts for different local and regional vaccination strategies.

mendel icon mendel

Genetic Aglorithm framework in Python.

napari-oif icon napari-oif

Napari plugin to read Olympus Image Formats images into napari

ncfs icon ncfs

Python implementation of Neighborhood Component Feature Selection (NCFS).

sotn icon sotn

Code for detecting SOTN in field recordings.

statisticallearning icon statisticallearning

Repository to learn Julia by implementing algorithms described in "The Elements of Statistical Learning: Data Mining, Inference, and Prediction" Second Edition by Trevor Hastie, Robert Tibshirani, and Jerome Friedman.

tn_test icon tn_test

post-clustering differential expression test

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