SolisLemus lab projects

BayesianNetworkRegression.jl

bioklustering

BioKlustering: a web app for semi-supervised learning of maximally unbalanced genomic data

dna-nn-theory

Here, we investigate the robustness, generalization potential and prediction accuracy of widely used convolutional neural network and natural language processing models with a variety of heterogeneous genomic datasets.

HighDimMixedModels.jl

Julia package for fitting regularized linear mixed-effect models on high-dimensional omics data.

lab-dynamics

Useful documents on guidelines, advice, resources for the lab

minaa

MiNAA aligns a pair of networks based their topologies and biologies.

mycovirus-ml

Machine-learning tools for mycovirus data

PhyloDiamond.jl

Method to estimate phylogenetic networks from algebraic invariants

snaq-tutorial

Tutorial to infer phylogenetic networks from multilocus data with SNaQ in PhyloNetworks

tropical-stethoscope

Classification of animal sounds in a hyperdiverse rainforest using Convolutional Neural Networks (Sun et al, 2021)

solislemuslab/mycovirus-ml

Machine-learning tools for mycovirus data

solislemuslab/dna-nn

Machine-learning methods (in particular neural networks) on DNA sequence input data for microbial datasets (in collaboration with Tim Read and Sam Brown)

solislemuslab/staph-nn

Neural network models for staph data (in collaboration with Tim Read)

solislemuslab/snaq-covid

Testing the limits of snaq with covid19 dataset

solislemuslab/colonization-squid

Studying the colonization factors of bacteria in squid (in collaboration with Mark Mandel)

solislemuslab/Graphical-abstracts

Source(?) of graphical abstracts of publications

solislemuslab/high-dim-stat-microbiome

solislemuslab/potato-lankau

Potato dataset: statistical and machine learning analyses in collaboration with Rick Lankau

solislemuslab/soil-network-koch

Collaboration with Paul Koch on effect of fungicides on soil microbes