Indy Big Data Conference 2018

With the recent influx of genomic data due to decreased sequencing costs and greater compute power, researchers are leveraging a wide range machine learning tools to find unique insights from their data. Due to the massive feature space of genomic data, some traditional statistical algorithms are inefficient or struggle to produce meaningful results. At Lifeomic, we have built a highly distributed machine learning system to address the many scalability problems found with processing and analyzing genomic and patient data, leveraging tools such as Apache Spark, Tensorflow, and custom hyper optimization algorithms.