Marinka Zitnik

Fusing bits and DNA

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Neural Embeddings

Article: To Embed or Not: Network Embedding as a Paradigm in Computational Biology

Current technology is producing high throughput biomedical data at an ever-growing rate. A common approach to interpreting such data is through network-based analyses. Since biological networks are notoriously complex and hard to decipher, a growing...

Article: Submit to ICLR 2019 Workshop on Representation Learning on Graphs and Manifolds

Many scientific fields study data with an underlying graph or manifold structure—such as protein networks, sensor networks, and biomedical knowledge graphs. The need for new optimization methods and neural network architectures that can accommodate t...

Article: ICLR 2019 Workshop: Representation Learning on Graphs and Manifolds

I am very excited to be co-organizing an ICLR 2019 workshop on Representation Learning on Graphs and Manifolds. We will be having an amazing lineup of invited speakers on a variety of methods and problems in this area! Also, stay tuned for the...

Article: Bioinformatics: What side effects to expect if taking multiple drugs?

Many patients take multiple drugs at the same time to treat complex diseases, such as heart failure, or co-occurring diseases, such as diabetes and epilepsy. The use of combinations of drugs is a common practice. In fact, 25 percent of people ages 65...

Article: Tutorial on Representation Learning for Network Biology

I am excited to announce that our tutorial on Representation learning for network biology is accepted at ISMB 2018. I will present the tutorial at ISMB 2018 conference in Chicago, IL. Stay tuned for more information and tutorial materials. Networks...

Article: Graph Convolutional Networks for Computational Pharmacology

Our paper on graph convolutional networks for modeling polypharmacy side effects has been accepted to ISMB conference. Stay tuned for the final version published in Bioinformatics journal. We describe a general graph convolutional neural network...

Article: ISMB/ECCB 2017: Feature Learning in Multi-layer Tissue Networks

I am giving a talk on feature learning in multi-layer tissue networks and tissue-specific protein function prediction at ISMB/ECCB. Check out the slides, the poster and the recorded talk.

Article: Understanding Protein Functions in Different Biological Contexts

Our paper on predicting multicellular function through multi-layer tissue networks is published in Bioinformatics and is included in the proceedings of ISMB/ECCB 2017, a premier conference in bioinformatics and computational biology. Understanding...

Article: Invited Talk on Uncovering Cellular Functions Through Multi-Layer Tissue Networks

I'm giving an invited talk on discovering gene functions through multi-layer tissue networks at the Network Medicine meeting at NetSci 2017. Check out the slides.