Perspective: Julia for Biologists

Overview

Perspective: Julia for Biologists

1. Examples

Speed: Example 1 - Single cell data and network inference

  • Domain: Single cell data
  • Methodology: Network inference
  • Feature: Speed for vectorisable code
  • Packages: InformationMeasures.jl

Speed: Example 2 - Dynamical systems and pharmacology

  • Domain: Pharmacology
  • Methodology: Dynamical systems
  • Feature: Speed for non linear system code
  • Packages: DifferentialEquations.jl

Abstraction: Example 1 - Structural bioinformatics

  • Domain: Structural bioinformatics
  • Methodology: Alignments, protein structure
  • Feature: Package composability
  • Packages: BioStructures.jl, BioSequences.jl, Bio3DViewer.jl, MetaGraphs.jl, LightGraphs.jl

Abstraction: Example 2 - Image processing in Julia

Metaprogramming: Example - Biochemical reaction networks

  • Domain: Biochemistry
  • Methodology: Dynamical systems
  • Feature: Metaprogramming
  • Packages: DifferentialEquations.jl, Catalyst.jl, GpABC.jl, Turing.jl

2. Links for learning more about Julia

General resources

Intermediate language features

Switching to Julia

Julia for biologists

Community

Owner
Elisabeth Roesch
Researcher + Theoretical(ly) Biologist @MelbIntGen/@unimelb, Maschinenlehrerin, Bayesian statistics, Developmental biology.
Elisabeth Roesch
Utilities to bridge Canvas-generated course rosters with GitLab's API.

gitlab-canvas-utils A collection of scripts originally written for CSE 13S. Oversees everything from GitLab course group creation, student repository

Eugene Chou 5 Jun 08, 2022
Image reconstruction done with untrained neural networks.

PyTorch Deep Image Prior An implementation of image reconstruction methods from Deep Image Prior (Ulyanov et al., 2017) in PyTorch. The point of the p

Atiyo Ghosh 192 Nov 30, 2022
The official PyTorch code implementation of "Personalized Trajectory Prediction via Distribution Discrimination" in ICCV 2021.

Personalized Trajectory Prediction via Distribution Discrimination (DisDis) The official PyTorch code implementation of "Personalized Trajectory Predi

25 Dec 20, 2022
This repository implements variational graph auto encoder by Thomas Kipf.

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DaehanKim 215 Jan 02, 2023
Code for "Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency" paper

UNICORN 🦄 Webpage | Paper | BibTex PyTorch implementation of "Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency" pap

118 Jan 06, 2023
Tutel MoE: An Optimized Mixture-of-Experts Implementation

Project Tutel Tutel MoE: An Optimized Mixture-of-Experts Implementation. Supported Framework: Pytorch Supported GPUs: CUDA(fp32 + fp16), ROCm(fp32) Ho

Microsoft 344 Dec 29, 2022
Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)

ProbAI 2021 - Probabilistic Programming and Variational Inference Tutorial with Pryo Day 1 (June 14) Slides Notebook: students_PPLs_Intro Notebook: so

PGM-Lab 46 Nov 01, 2022
A Confidence-based Iterative Solver of Depths and Surface Normals for Deep Multi-view Stereo

idn-solver Paper | Project Page This repository contains the code release of our ICCV 2021 paper: A Confidence-based Iterative Solver of Depths and Su

zhaowang 43 Nov 17, 2022
Official implementation of Sparse Transformer-based Action Recognition

STAR Official implementation of S parse T ransformer-based A ction R ecognition Dataset download NTU RGB+D 60 action recognition of 2D/3D skeleton fro

Chonghan_Lee 15 Nov 02, 2022
A deep learning network built with TensorFlow and Keras to classify gender and estimate age.

Convolutional Neural Network (CNN). This repository contains a source code of a deep learning network built with TensorFlow and Keras to classify gend

Pawel Dziemiach 1 Dec 19, 2021
Segcache: a memory-efficient and scalable in-memory key-value cache for small objects

Segcache: a memory-efficient and scalable in-memory key-value cache for small objects This repo contains the code of Segcache described in the followi

TheSys Group @ CMU CS 78 Jan 07, 2023
Code release for The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification (TIP 2020)

The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification Code release for The Devil is in the Channels: Mutual-Channel

PRIS-CV: Computer Vision Group 230 Dec 31, 2022
The audio-video synchronization of MKV Container Format is exploited to achieve data hiding

The audio-video synchronization of MKV Container Format is exploited to achieve data hiding, where the hidden data can be utilized for various management purposes, including hyper-linking, annotation

Maxim Zaika 1 Nov 17, 2021
text_recognition_toolbox: The reimplementation of a series of classical scene text recognition papers with Pytorch in a uniform way.

text recognition toolbox 1. 项目介绍 该项目是基于pytorch深度学习框架,以统一的改写方式实现了以下6篇经典的文字识别论文,论文的详情如下。该项目会持续进行更新,欢迎大家提出问题以及对代码进行贡献。 模型 论文标题 发表年份 模型方法划分 CRNN 《An End-t

168 Dec 24, 2022
GNEE - GAT Neural Event Embeddings

GNEE - GAT Neural Event Embeddings This repository contains source code for the GNEE (GAT Neural Event Embeddings) method introduced in the paper: "Se

João Pedro Rodrigues Mattos 0 Sep 15, 2021
This is the code of paper ``Contrastive Coding for Active Learning under Class Distribution Mismatch'' with python.

Contrastive Coding for Active Learning under Class Distribution Mismatch Official PyTorch implementation of ["Contrastive Coding for Active Learning u

21 Dec 22, 2022
A large-image collection explorer and fast classification tool

IMAX: Interactive Multi-image Analysis eXplorer This is an interactive tool for visualize and classify multiple images at a time. It written in Python

Matias Carrasco Kind 23 Dec 16, 2022
Release of the ConditionalQA dataset

ConditionalQA Datasets accompanying the paper ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers. Disclaimer This dataset

14 Oct 17, 2022
Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

keven 198 Dec 20, 2022
Autonomous Movement from Simultaneous Localization and Mapping

Autonomous Movement from Simultaneous Localization and Mapping About us Built by a group of Clarkson University students with the help from Professor

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