#335: Gene Editing with Python

1

Introduction

00:00 • 2min

2

How Did You Get Into Python?

01:39 • 2min

3

Genetic Medicine

03:54 • 2min

4

The Future of Biotechnology

05:53 • 2min

5

How to Cure a Sickle Cell Disease?

08:21 • 3min

6

Next Generation Sequencing

10:54 • 2min

7

How Much Data Is in D and A?

12:37 • 2min

8

The Challenges of a Data Processing Pipeline

14:27 • 2min

9

Project Management With Robots

16:41 • 3min

10

Getting Data From the Cloud Into the Machines

19:40 • 2min

11

Using the Event Streaming Lamda Functions in the Cloud

21:27 • 3min

12

Impo Structure Is Good Bits Theata

24:21 • 3min

13

Creating Data Pipelines in the Cloud

26:56 • 2min

14

Sequencing Assays - What's the Process?

29:09 • 2min

15

Using a Workflow Manager

30:41 • 3min

16

What's the Process of Moving to Production?

33:17 • 2min

17

Is Luigi the Best Workflow Manager?

35:16 • 2min

18

Airflow and Luigireny Workfu Manasure

37:43 • 2min

19

Is It Possible to Scale Up a W S Batch?

39:33 • 2min

20

The Scale of the Cloud

41:30 • 2min

21

Is That the Right Version of the Code?

43:49 • 3min

22

The Cost of Doing Business Ages

46:25 • 1min

23

Data Store

47:54 • 2min

24

Using a Mongo Engine to Do Sequent Base Searches?

50:04 • 2min

25

The Pyphon Data Classes Are a Great Tool for Interoperability

51:53 • 2min

26

Using a C D K on a Datapy Plan?

53:55 • 2min

27

How to Get Started With Python Scripting

55:37 • 2min