Latent Models

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 a...

Article: Jozef Stefan Golden Emblem Prize

I am honored to receive Jozef Stefan Golden Emblem for winning PhD dissertation in the fields of natural sciences, medicine and biotechnology. The prize is awarded by Jozef Stefan Institute. I look forward to making further progress on machine...

Article: PSB 2016: Collective Pairwise Classification for Multi-Way Analysis

Our paper on Collective Pairwise Classification for Multi-Way Analysis has been published in the Proceedings of the 21st Pacific Symposium on Biocomputing. We will present the work at the PSB conference in January 2016. In the paper, we develop a...

Article: PLoS CompBio: Gene Prioritization by Compressive Data Fusion

Our paper on Gene prioritization by compressive data fusion and chaining has been published in PLoS Computational Biology. In the paper, we present Collage, a new data fusion approach to gene prioritization. Together with collaborators from Baylor...

Article: Data Fusion Tutorial at the IEEE Engineering in Medicine and Biology

Together with Blaz Zupan we organize a tutorial on data fusion at the International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). In the tutorial, we will explore latent factor models, a popular class of approaches that...

Article: ACM XRDS: Understanding Cancer with Matrix Factorization

The Summer issue of ACM XRDS is here! In this issue we write about computational biology. Our features and interviews present different perspectives about some of the most recent advances of computational biology. You can read about personalized...

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: ISMB 2015: Integrate Everything but the Kitchen Sink

Our poster at ISMB 2015 is concerned with data set selection and sensitivity estimation in collective factor models. Molecular biology data is rich in volume as well as heterogeneity. We can view individual data sets as relations between objects of...

Article: Compressive Data Fusion and Persistent Homology

My talk at the Summer School on Computational Topology in Ljubljana, Slovenia was about coupling compressive data fusion methods with algebraic topology, in particular persistent homology. There, I discussed how the latent data space obtained by fusi...

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...

Article: Poster Award at the Basel Computational Biology Conference

Our poster on Gene prioritization by compressive data fusion and chaining got best poster award at the Basel Computational Biology Conference ([BC]^2). The poster highlights our recent computational method that prioritizes genes by fusing...

Article: Data Fusion Tutorial at the Basel Computational Biology Conference

Together with Blaz Zupan we organize a tutorial on data fusion at the Basel Computational Biology Conference ([BC]^2). The tutorial is targeted at computational scientists, data mining researchers and molecular biologists interested in large-scale...

Article: Syst Biomed: Survival Regression by Data Fusion

Our recent paper in Systems Biomedicine describes a new computational approach that predicts patient’s survival time from a collection of heterogeneous data sets. This is the full paper of our award winning entry at CAMDA meeting at ISMB 2014, Boston...

Article: J Comp Biol: Network-Guided Matrix Completion

Our recent paper in Journal of Computational Biology introduces an interaction data imputation method called network-guided matrix completion (NG-MC). The core part of NG-MC is low-rank probabilistic matrix completion that incorporates prior knowledg...

Article: IEEE TPAMI: Data Fusion by Matrix Factorization

We recently published a paper on a new data fusion method in IEEE Transactions on Pattern Analysis and Machine Intelligence. For most problems in science and engineering we can obtain data sets that describe the observed system from various...

Article: @Stanford University, Department of Computer Science

I am visiting the Department of Computer Science at Stanford University, CA, USA in Summer and Fall 2014. During my stay we will study the interplay between network analysis, data integration and biology. There are many exciting challenges one ca...

Article: CAMDA 2014: Survival Regression by Data Fusion

I have presented at CAMDA 2014 an extension of our recent matrix factorization-based data fusion approach that couples data fusion with survival regression. CAMDA 2014 runs as a satellite meeting at ISMB 2014, Boston, MA, USA. Our presentation got...

Article: @RECOMB 2014, Pittsburgh, PA (Part II)

We are presenting a poster about our recent data fusion methodology (ArXiv preprint) at RECOMB Conference. Thanks to Prof. Blaz Zupan for the storyline and Prof. Richard H. Kessin for valuable comments. xkcd.com served as an inspiration of poster...

Article: @RECOMB 2014, Pittsburgh, PA (Part I)

We got accepted a paper on Imputation of Quantitative Genetic Interactions in Epistatic MAPs by Interaction Propagation Matrix Completion to RECOMB 2014. Epistatic Miniarray Profile (E-MAP) is a popular large-scale gene interaction discovery...