ruvnet

A comprehensive implementation of an Ai powered genetic testing platform, complete with detailed instructions and documentation. This guide will walk you through setting up each component, ensuring a fully functional system.

Table of Contents

1. System Overview
2. Project Structure
3. Environment Setup
4. Configuration Management
5. Database Integration
6. MinION Controller Implementation

comp500

This list has moved!

See https://github.com/comp500/fabric-serverside-mods for the latest mod list!

npearce

UPDATE (March 2020, thanks @ic): I don't know the exact AMI version but yum install docker now works on the latest Amazon Linux 2. The instructions below may still be relevant depending on the vintage AMI you are using.

Amazon changed the install in Linux 2. One no-longer using 'yum' See: https://aws.amazon.com/amazon-linux-2/release-notes/

Docker CE Install

sudo amazon-linux-extras install docker
sudo service docker start

kauffmanes

Thanks everyone for commenting/contributing! I made this in college for a class and I no longer really use the technology. I encourage you all to help each other, but I probably won't be answering questions anymore.

This article is also on my blog: https://emilykauffman.com/blog/install-anaconda-on-wsl

Note: $ denotes the start of a command. Don't actually type this.

Steps to Install Anaconda on Windows Ubuntu Terminal

1. Install WSL (Ubuntu for Windows - can be found in Windows Store). I recommend the latest version (I'm using 18.04) because there are some bugs they worked out during 14/16 (microsoft/WSL#785)
2. Go to https://repo.continuum.io/archive to find the list of Anaconda releases
3. Select the release you want. I have a 64-bit computer, so I chose the latest release ending in x86_64.sh. If I had a 32-bit computer, I'd select the x86.sh version. If you accidentally try to install the wrong one, you'll get a warning in the terminal. I chose `Anaconda3-5.2.0-Li

moisadoru

#/bin/bash

# Installs libfreetype6 2.8.0 into affected electron app.
# For more details ee:
#   https://github.com/atom/atom/issues/15737
#   https://github.com/Microsoft/vscode/issues/35675

CRT=$(dpkg-query --showformat='${Version}' --show libfreetype6)
CRT=$(echo $CRT | sed -e 's/-.*$//g')

jkatz

#!/bin/bash

mkdir postgres
cd postgres

docker volume create --driver local --name=pgvolume
docker volume create --driver local --name=pga4volume

docker network create --driver bridge pgnetwork

yufengg

dlebech

# Public Domain CC0 license. https://creativecommons.org/publicdomain/zero/1.0/
"""MongoDB Apache Beam IO utilities.

Tested with google-cloud-dataflow package version 2.0.0

"""

__all__ = ['ReadFromMongo']

import datetime

gyglim

"""Simple example on how to log scalars and images to tensorboard without tensor ops.

License: BSD License 2.0
"""
__author__ = "Michael Gygli"

import tensorflow as tf
from StringIO import StringIO
import matplotlib.pyplot as plt
import numpy as np

ravibhure

In your local clone of your forked repository, you can add the original GitHub repository as a "remote". ("Remotes" are like nicknames for the URLs of repositories - origin is one, for example.) Then you can fetch all the branches from that upstream repository, and rebase your work to continue working on the upstream version. In terms of commands that might look like:

Add the remote, call it "upstream":

git remote add upstream https://github.com/whoever/whatever.git

Fetch all the branches of that remote into remote-tracking branches, such as upstream/master:

git fetch upstream