This document discusses software testing in the life sciences domain. It notes that life sciences data involves large volumes of data that can be represented in different ways. While there are engineering issues to consider when testing life sciences software, the principles of testing do not differ. Examples are given of types of life sciences software like genome browsers and molecular viewers. The document provides suggestions for test data sources and discusses tools and languages commonly used for automated testing of life sciences software like Java, Selenium, and Python. It also highlights some challenges in automating the testing of things like canvas elements and 3D models. Links are provided to open source projects and demos from EPAM as examples.