HasiHays
Computational Systems Biology, Systems Medicine
University of ArkansasFayetteville, Arkansas, USA
Pinned Repositories
2020plus
Classifies genes as an oncogene, tumor suppressor gene, or as a non-driver gene by using Random Forests
awesome-biology
Curated (meta)list of resources for Biology.
awesome-cheminformatics
A curated list of Cheminformatics libraries and software.
awesome_spatial_omics
tools and notes for spatial omics
breast-cancer-sub-types
A novel self-supervised feature extraction method using omics data is proposed which improves classification in most of the classifiers.
CellClassificationMachineLearning
Single Cell Classification using RNA-seq data and Supervised Learning Algorithms
cheminformatics
Facilitates searching, screening, and organizing large chemical databases
Computational-Medicine
PyBioNetGen
A simple CLI for BioNetGen
scRNA-tools
Table of software for the analysis of single-cell RNA-seq data.
HasiHays's Repositories
HasiHays/anndata2ri
Convert between AnnData and SingleCellExperiment
HasiHays/BayesSpace
Bayesian model for clustering and enhancing the resolution of spatial gene expression experiments.
HasiHays/Binance-Futures-Trading-Bot
A Technical Analysis Bot that trades leveraged USDT futures markets on Binance.
HasiHays/cell-free-book
Book PDF and simulation code for the monograph "Foundations of User-Centric Cell-Free Massive MIMO" by Özlem Tugfe Demir, Emil Björnson and Luca Sanguinetti, published in Foundations and Trends in Signal Processing, 2021.
HasiHays/Cell_Signaling_Pathway_Simulator
A simulation for teaching the protein synthesis cell signaling pathway to introductory biology students.
HasiHays/cellrank
CellRank: dynamics from multi-view single-cell data
HasiHays/cellxgene_VIP
Enables cellxgene to generate violin, stacked violin, stacked bar, heatmap, volcano, embedding, dot, track, density, 2D density, sankey and dual-gene plot in high-resolution SVG/PNG format. It also performs differential gene expression analysis and provides a Command Line Interface (CLI) for advanced users to perform analysis using python and R.
HasiHays/codax
Neural Logic ODEs for Cell Signaling Inference with JAX
HasiHays/CollecTRI
Gene regulatory network containing signed transcription factor-target gene interactions
HasiHays/FICT
FISH Iterative Cell Typing
HasiHays/gennifer-grnboost2
HasiHays/Homogeneous-and-heterogenous-networks
This code was performed for the analysis of calcium signals fromencodrine cells during different hormonal stimuli
HasiHays/infercnv
Inferring CNV from Single-Cell RNA-Seq
HasiHays/infercnvpy
Infer copy number variation (CNV) from scRNA-seq data. Plays nicely with Scanpy.
HasiHays/Intro-to-rnaseq-hpc-salmon-flipped
Introduction to bulk RNA-seq
HasiHays/kinet_annotate
cell annotation and kinetochore signal measurement guide
HasiHays/liana
LIANA: a LIgand-receptor ANalysis frAmework
HasiHays/mistyR
Multiview Intercellular SpaTial modeling framework
HasiHays/Nuwa
A bioinformatics web app for single cell RNA seq analysis.
HasiHays/pagoda2
R package for analyzing and interactively exploring large-scale single-cell RNA-seq datasets
HasiHays/parallels-desktop
This is the crack version of parallels desktop
HasiHays/scGIST
HasiHays/SingleCellExperiment
Clone of the Bioconductor repository for the SingleCellExperiment package, see https://bioconductor.org/packages/devel/bioc/html/SingleCellExperiment.html for the official development version.
HasiHays/smart-money-concepts
This is a python package for smart money concept indicators
HasiHays/SpatialDE
Test genes for Spatial Variation
HasiHays/squidpy
Spatial Single Cell Analysis in Python
HasiHays/text2model-from-knowledge
Extending BioMASS to construct mathematical models from external knowledge (Arakane et al., 2024)
HasiHays/trading-futures-tradingview-script
I write pine script to trade futures ES1 NQ1 with signal IN (accurate 90%) and now I am trading on that
HasiHays/workshop-scRNAseq
Single cell RNA sequencing analysis course
HasiHays/wormneuroatlas
Neural signal propagation atlas (Randi et al.), genome (WormBase), single-cell transcriptome (Taylor et al.), neuropeptide/GPCR deorphanization (Beets et al.), monoaminergic connectome (Bentley et al.), and chemical-synapse sign predictions (Fenyves et al.) all in one place. Read the docs: https://francescorandi.github.io/wormneuroatlas/