{"action":"created","issue":{"url":"https://api.github.com/repos/NLeSC/TEAM2018/issues/42","repository_url":"https://api.github.com/repos/NLeSC/TEAM2018","labels_url":"https://api.github.com/repos/NLeSC/TEAM2018/issues/42/labels{/name}","comments_url":"https://api.github.com/repos/NLeSC/TEAM2018/issues/42/comments","events_url":"https://api.github.com/repos/NLeSC/TEAM2018/issues/42/events","html_url":"https://github.com/NLeSC/TEAM2018/issues/42","id":380229343,"node_id":"MDU6SXNzdWUzODAyMjkzNDM=","number":42,"title":"Paper 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could you provide a bit more info about the paper you will work on? Would some help be welcomed or do you plan to work alone on it?"},"comment":{"url":"https://api.github.com/repos/NLeSC/TEAM2018/issues/comments/438658280","html_url":"https://github.com/NLeSC/TEAM2018/issues/42#issuecomment-438658280","issue_url":"https://api.github.com/repos/NLeSC/TEAM2018/issues/42","id":438658280,"node_id":"MDEyOklzc3VlQ29tbWVudDQzODY1ODI4MA==","user":{"login":"NicoRenaud","id":24918192,"node_id":"MDQ6VXNlcjI0OTE4MTky","avatar_url":"https://avatars1.githubusercontent.com/u/24918192?v=4","gravatar_id":"","url":"https://api.github.com/users/NicoRenaud","html_url":"https://github.com/NicoRenaud","followers_url":"https://api.github.com/users/NicoRenaud/followers","following_url":"https://api.github.com/users/NicoRenaud/following{/other_user}","gists_url":"https://api.github.com/users/NicoRenaud/gists{/gist_id}","starred_url":"https://api.github.com/users/NicoRenaud/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/NicoRenaud/subscriptions","organizations_url":"https://api.github.com/users/NicoRenaud/orgs","repos_url":"https://api.github.com/users/NicoRenaud/repos","events_url":"https://api.github.com/users/NicoRenaud/events{/privacy}","received_events_url":"https://api.github.com/users/NicoRenaud/received_events","type":"User","site_admin":false},"created_at":"2018-11-14T13:17:45Z","updated_at":"2018-11-14T13:17:45Z","author_association":"NONE","body":"@romulogoncalves the paper is on a graph-based method using Support Vector Machine to classify protein-protein interfaces. \r\n\r\nThe software compute graphs of protein interfaces, kernels between pairs of graphs and use the kernels to train a model with SVM (using libsvm under the hood). The model can then used to predict the quality of new protein interfaces. A simple command line interface greatly facilitate the workflow and can compute graphs and kernels in parallel (using mpi4py).\r\n\r\nThe computation of the graph kernel can be done with a (rather simple) GPU implementation that I'm still trying to improve (the Kernel Tuner can be used to fine tune there).\r\n\r\nI've worked on that project only with people from Utrecht so I would rather work alone on it."}}
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