[et_pb_section fb_built=”1″ _builder_version=”4.0.2″][et_pb_row _builder_version=”4.0.2″ border_width_all=”6px” border_color_all=”#8b68ee”][et_pb_column type=”4_4″ _builder_version=”4.0.2″][et_pb_text _builder_version=”4.0.2″ background_enable_image=”off” background_size=”initial” min_height=”37px” custom_padding=”||0px|||” border_color_all=”#8b68ee”]<\/p>\n
[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.0.2″][et_pb_column type=”4_4″ _builder_version=”4.0.2″][et_pb_text _builder_version=”4.0.2″]<\/p>\n
This workshop intends to facilitate the training and discourse amongst bioinformatics researchers interested in machine learning using Galaxy. It will be a one-day event, including six sessions and during this workshop we will train researchers to use Galaxy for
machine learning analysis.<\/p>\n
The first session will provide an introduction to Galaxy. Galaxy is a scientific platform that helps scientists to analyse data without any programming skills. To analyse data, workflows can be created to make the analyses reproducible and shareable.<\/p>\n
In the second session, basic concepts in machine learning will be introduced.<\/p>\n
The next three sessions will serve as a hands-one sessions to follow training tutorials with case studies to see how classification algorithms, regression models and unsupervised learning methods in Galaxy can be used to solve real-world problems. In the last session, we will introduce feature selection and hyper parameter optimization methods in Galaxy and the workshop will be summing up at the end.<\/p>\n
<\/a>Topics<\/strong><\/p>\n Schedule<\/strong><\/p>\n 09:00 \u2013 09:45 Welcome and Introduction to Galaxy Target audience<\/strong><\/p>\n The target audience includes researchers interested in analysing biological data using machine learning algorithms and want to use machine learning for classification, regression and clustering tasks. Specifically, we encourage scholars that have begun biological data analysis and interested to know what is machine learning and how they can use Galaxy for machine learning tasks.<\/p>\n Contributions<\/strong><\/p>\n More information coming soon<\/p>\n Organizers<\/strong><\/p>\n Dr. Alireza Khanteymoori, Freiburg University, Germany Contact<\/strong><\/p>\n Dr. Alireza Khanteymoori [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.0.2″][et_pb_row _builder_version=”4.0.2″][et_pb_column type=”4_4″ _builder_version=”4.0.2″][et_pb_text _builder_version=”4.0.2″][\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.0.2″][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" TutorialsMachine Learning in Bioinformatics using Galaxy This workshop intends to facilitate the training and discourse amongst bioinformatics researchers interested in machine learning using Galaxy. It will be a one-day event, including six sessions and during this workshop we will train researchers to use Galaxy formachine learning analysis. The first session will provide an introduction to […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":""},"_links":{"self":[{"href":"https:\/\/easyconferences.eu\/iisa2020\/wp-json\/wp\/v2\/pages\/37"}],"collection":[{"href":"https:\/\/easyconferences.eu\/iisa2020\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/easyconferences.eu\/iisa2020\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/easyconferences.eu\/iisa2020\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/easyconferences.eu\/iisa2020\/wp-json\/wp\/v2\/comments?post=37"}],"version-history":[{"count":6,"href":"https:\/\/easyconferences.eu\/iisa2020\/wp-json\/wp\/v2\/pages\/37\/revisions"}],"predecessor-version":[{"id":405,"href":"https:\/\/easyconferences.eu\/iisa2020\/wp-json\/wp\/v2\/pages\/37\/revisions\/405"}],"wp:attachment":[{"href":"https:\/\/easyconferences.eu\/iisa2020\/wp-json\/wp\/v2\/media?parent=37"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n
random forest)<\/li>\n
09:45 \u2013 10.30\u00a0 Machine Learning Basics
10:30 \u2013 10:45\u00a0 Coffee Break
10:45 \u2013 12:15\u00a0 \u00a0Classifiers
12:15 \u2013 13:30\u00a0 \u00a0Lunch Break
13:30 \u2013 15:00\u00a0 Regressors
15:00 \u2013 15:45\u00a0 Unsupervised Learning
15:45 \u2013 16:00\u00a0 Coffee Break
16:00 \u2013 16:45\u00a0 Feature Selection and Hyper parameter Optimization
16:45 \u2013 17:00\u00a0 Conclusion<\/p>\n
Dr. Bj\u00f6rn Gr\u00fcning,\u00a0Freiburg University, Germany
Anup Kumar,\u00a0Freiburg University, Germany<\/p>\n
Email: khanteymoori@gmail.com<\/a>, alireza@informatik.uni-freiburg.de<\/a>\u00a0<\/p>\n