Marinka Zitnik

Fusing bits and DNA

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Article: Guest Lecture on Graph Convolutional Networks

I have had the opportunity to give a lecture on Graph Convolutional Networks in the CS224W class (Analysis of Networks: Mining and Learning with Graphs) at Stanford. Here are slides and video of the lecture.

Article: Evolution of Protein Interactomes across the Tree of Life

The interactome network of protein-protein interactions captures the structure of molecular machinery and gives rise to a bewildering degree of life complexity. We composed and analyzed interactome networks from 1,840 species across the tree of life,...

Article: Nature Communications: General Method to Denoise Biological Networks

Technical noise in experiments is unavoidable, but it introduces inaccuracies into the biological networks we infer from the data. In this Nature Communications paper, we introduce a diffusion-based method for denoising undirected, weighted networks,...

Article: ISMB 2018: Polypharmacy Side Effects

We presented our work on predicting polypharmacy side effects at ISMB/ECCB in Chicago, IL, USA. Here are the slides. This work has been highlighted in Stanford News, covered by several other news outlets, and is the most read paper in Bioinformatics....

Article: Tutorial on Deep Learning for Network Biology at ISMB

We just presented a tutorial on Deep Learning for Network Biology at ISMB 2018 in Chicago, IL, USA. If you are interested in these topics and would like to learn more about graph neural networks and/or their biomedical applications but could not...

Article: Nature Communications: Prioritizing Network Communities

Community detection allows one to decompose a network into its building blocks. While communities can be identified with a variety of methods, their relative importance cannot be easily derived. In this Nature Communications paper, we introduce an...

Article: Submit to Frontiers in Genetics: Single-Cell Data Analytics

I am thrilled about an opportunity to co-edit a research topic on single-cell data analytics, resources, challenges and perspectives for Frontiers in Genetics! With this research topic, we aim to provide a broad coverage of single-cell data analytic...

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: JMM 2018: Invited Talk on Prioritization of Network Communities

I am giving a talk on prioritization of network communities, a framework that enables speeding-up scientific discovery process in experimental network sciences. It is very exciting to be able to present this challenging and important problem at...

Article: PSB 2018: Disease Pathways in the Human Interactome

I am giving a talk on large-scale analysis of disease pathways in the human interactome at PSB. Check out my slides, poster and the paper if interested or want to learn more about disease pathway prediction, learning using biological data, and ...

Article: Guest Lecture on Biological Network Analysis

I am giving a guest lecture on biological network analysis in the CS224W Network Analysis course at Stanford. The lecture introduces biological networks and their analysis to the CS and engineering students. It describes statistical enrichment tests...

Article: PSB 2018: Large-Scale Analysis of Disease Pathways in the Human Interactome

Our paper on large-scale analysis of disease pathways in the human interactome will appear at Pacific Symposium on Biocomputing. Discovering disease pathways, which can be defined as sets of proteins associated with a given disease, is an important...

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: 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.

Article: Invited Talk on Boosting Biomedical Discovery Through Network Data Analytics

I'm giving an invited talk on speeding-up scientific discovery in biomedicine through computational network analytics at the International Conference for Big Data and AI in Medicine.

Article: ACM XRDS: The Brownian Wanderlust of Things

The Spring issue of ACM XRDS is here! This issue is centered around digital fabrication, which in many ways highlights the expanded role of computer in today's society. Digital fabrication is not merely about 3D printing knickknacks, rather it enables...

Article: ACM XRDS: The Marvel Comic Book Universe

The Fall issue of ACM XRDS is here! In this issue we write about virtual reality. Among others, you can read about the virtual reality revolution and ways to bring virtual reality home. The issue also discusses how to use your own muscles to achieve...

Article: ISMB 2015: Gene Network Inference via Data Fusion

Our paper at ISMB 2015 addresses a challenging task of inferring gene networks by taking into consideration potentially many data sets. Importantly, these data sets might be nonidentically distributed and can follow any combination of exponential...

Article: Bioinformatics: Gene Network Inference by Fusing Diverse Distributions

Our paper on Gene network inference by fusing data from diverse distributions has been published in Bioinformatics. We will present it at ISMB 2015 in Dublin. In the paper we describe FuseNet, a Markov network formulation that infers networks from a...

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