title: “Causal structure learning under unfaithfulness.” abstract:” Inferring from experimental data the causal relations among variables is a scientific important but challenging task. One of the approaches relies on the probabilistic independencies between variables. Algorithms have been designed that allow the construction of the causal model of the system. Although powerful, one of the fundamental […]
Between January 19 – 22, 2016, Yannis Pantazis attended as an invited speaker the “Uncertainty Quantification for Multiscale Stochastic Systems and Applications” workshop held at IPAM, UCLA. The title of the talk was “Sensitivity analysis, uncertainty quantification and inference in stochastic dynamics“.
The 13th Hellenic Congress of Clinical Chemistry is held in Heraklion Crete, October 29-31, 2015. MXM participates with an invited lecture by Professor Tsamardinos: “Bionformatics advances for automating predictive biomarker and biosignatures from data”. Program of the congress: program.pdf .
The EU funded STATegra project has come to its end, after three years of intense research and development of novel statistical methods for the integration of heterogeneous omics data. Information regarding the objectives of the project, the activities carried in these three years and the scientific and commercial outcomes are available on the project website: […]
The STATegra Summer School in Omics and Data Integration has been held in Benicassim, Spain, from the 7th to the 11th of September 2015, providing training to more than 30 among experimentalists and bioinformaticians in the analysis of multi-omics experiments. Further information on the summer school website: http://stategrasummerschool.com/
The second edition of the “Statistical Methods for Omics Data Integration and Analysis” conference has been held in Valencia, September 14-16, 2015. MXM has participated with a talk regarding application of data-integration methods for the analysis of public microarray data in Leukemia patients. The program of the conference and further information on SMODIA2015 website: http://smodia2015.cipf.es/
“Use of single cell proteomics measurements for elucidation of biomolecular regulatory networks” Speaker: Karen Sachs, Stanford University School of Medicine Date: 03 September 2015 Time: 11:00 – 13:00 Location: Seminar Room I, FORTH, Heraklion, Crete Host: Ioannis Tsamardinos Abstract: We have previously introduced the application of probabilistic models for elucidation of statistical relationships from single […]
From July 1st to July 3rd, Yannis Pantazis attended the workshop “Mathematical Trends in Reaction Network Theory” at Copenhagen, Denmark. He presented a poster entitled “Pathwise Information-theoretic Metrics for Parametric Sensitivity Analysis” where the relative entropy rate and the associated path Fisher information matrix were demonstrated as a means of assessing the parameters’ sensitivities.
“Methods for massive multiple testing under dependence” Speaker: Alessio Farcomeni, Assistant Professor in Medical Statistics at Sapienza University of Rome Date: 30 April 2015 Time: 12:00 – 13:00 Location: Seminar Room I, FORTH, Heraklion, Crete Host: Ioannis Tsamardinos Abstract: Issues about the global level arise whenever many hypotheses are tested at once. A common approach […]
Our work has been awarded with the Boeringer Ingelheim Cancer Research Award (Best Abstract / Poster of the Year) 2014 from the Norwegian Lung Cancer Group. This is joint work with our NTNU collaborators involving the analysis of case-control molecular profiles of lung cancer from the HUNT biobank. For more information see http://www.nlcg.no/node/122. The poster […]
As of 1-1-2015 the Bioinformatics Laboratory of the Institute of Computer Science at the Foundation for Research and Technology, Hellas has been merged with the Computational Medicine Laboratory to yield the Computational BioMedicine Laboratory (http://www.ics.forth.gr/cbml ) . The new laboratory’s Head is Dr. Kostas Marias. As the Head of the former Bioinformatics Laboratory, I (Prof. […]
On behalf of the STATegra consortium our group participated in the organization of a workshop titled “Statistical Methods for Omics Data Integration and Analysis, SMODIA”. The workshop took place in November 10-12, 2014 in Heraklion, Crete, Greece. It was organized as part of the dissemination efforts of the STATegra FP7 EU project, titled “User-driven Development […]
Eleni Sgouritsa presents her work on Tuesday, November 4th , 12:00pm, Seminar Room I, Institute of Computer Science, Foundation for Research and Technology Hellas (FORTH). Title: Identifying confounders and telling cause from effect using latent variable models Abstract: Drawing causal conclusions from observed statistical dependencies is a fundamental problem. Conditional independence-based causal discovery (e.g., PC […]
Pr. Ioannis Tsamardinos is invited to give a talk at MPI for Intelligent Systems in Tuebingen. Title: Advances in Integrative Causal Analysis Abstract: We’ll present the concept and approach of Integrative Causal Analysis(INCA), where causal models and relations are induced from multiple,heterogeneous datasets. The datasets maybe heterogeneous in terms of the variable sets they measure […]
Dr. Andreas Damianou presents his work on Tuesday, June 10th , 10:00am, Seminar Room 211, STEP-C, Institute of Computer Science, Foundation for Research and Technology Hellas (FORTH). Abstract: The high dimensional and complex nature of real world data makes them difficult to visualise, understand, predict and, in general, work with. Similarly, consolidating multiple distinct but […]
The ’MXM’ (Mens eX Machina, meaning ’Mind from the Machine’ in Latin) package is an R package that implements feature selection methods for identifying minimal, statistically-equivalent and equally-predictive feature subsets. The ’MXM’ package provides source code for the SES algorithm and for some appropriate statistical conditional independence tests (testIndFisher, testIndLogistic, gSquare and censIndLR are included). […]
On behalf of the STATegra consortium our group is participating in the organization of a workshop titled “Statistical Methods for Omics Data Integration and Analysis”. The workshop will take place in November 10-12, 2014 in Heraklion, Crete, Greece. It is organized as part of the dissemination efforts of the STATegra FP7 EU project, titled “User-driven Development […]
Professor Ioannis Tsamardinos is one of the organizers of the Paramet Summer School- Computational Sciences in Drug Discovery. The workshop will take place in Heraklion, Crete, Greece, in The Foundation for Research and Technology (FORTH), from June 30 to July 4, 2014. Professor Ioannis Tsamardinos will give a lecture on Wednesday, July 2, titled “Identification […]
Associate Professor Ioannis Tsamardinos, received an ERC Consolidator Grant through the program “IDEAS” by the European Research Council (European Research Council ERC) for his research proposal titled: “Next Generation Causal Analysis: Inspired by the Induction of Biological Pathways from Cytometry Data”. The funding of the proposal will provide an opportunity to our group to develop […]
The research grant “EPILOGEAS”, titled “Causal-Based Variable Selection for Omics Data”, which was submitted in the Operational Programme “Education and Lifelong Learning 2007-2013” – Action “Excellence II”, has been approved for funding. The project is funded by the European Social Fund (ESF) and National Resources. Beneficiary of the project is the Foundation for Research and […]
Members of the IMBB institute and of the BIL lab are currently providing an introductory course to R open to FORTH researchers/post-doc/students/staff that rare interested in approaching the R software and language for the first time. The lessons will take place in the Γ100 room at 9:15 am every Wednesday.
Our group is presenting our latest discoveries and newly developed Causal Discovery algorithms in the workshop “Case Studies of Causal Discovery with Model Search”. The presentation will be recorded and be made publicly available. Some of this work stems from a close collaboration with our Karolinska Institutet STATegra partners in the Computational Medicine Unit. The […]
Our group participated in the first year’s STATegra project meeting, held in the Imperial College London. The meeting was a great success. Novel data will be available soon, while new methods and tools are continuously being developed by the consortium. New upcoming events will be held this March. STATegra has a new, updated web-site containing […]
This year, our group’s research has transcended the computer science and bioinformatics publishing forums and, through collaborations with prestigious biological groups, has participated in publications in high-impact journals of the biology community. The Garini’s lab research has shown that that DNA damage triggers a chronic auto-inflammatory response leading to fat depletion published in Cell Metabolism. […]
BIL has recently secured funding in competitive and exciting EU and Greek National research grants (BIOSYS by GSRT, eModia by GSRT, STATegra EU FP7, as well as participation in other grants). BIL is looking to expand by hiring ambitious, energetic, intelligent, and hard-working individuals to lead the development of novel machine learning methods, particularly for […]
Our group is participating in the new institutional grant on Systems Biology, named BIOSYS, coordinated by the Institute of Molecular Biology and Biotechnology of FORTH. The grant will provide more funding for developing causal discovery algorithms, as well as model selection algorithms for machine learning models. The algorithms will be packaged in tools for non-experts […]
Members of our group gave a tutorial on Causal Discovery, titled “An Introduction to Causal Discovery, a Bayesian Network Approach” in the recent the High-Throughput Omics and Data Integration Workshop organized by the STATegra projects and the COST Action SeqAHead. Apart from the introduction to the theory and algorithms of Causal Discovery, the tutorial covered […]
Sofia Triantafillou received one of the three Best Poster Awards in the recent 7th Conference of the Hellenic Society for Computational Biology and Bioinformatics (HSCBB12) for her poster titled “Predicting associations from multiple “omics” data sets”. The judging committee of the conference consisted of all the invited speakers of the conference.
New positions are available at FORTH within our group. We have secured funding in competitive and exciting EU research grants and are looking to expand by hiring ambitious, energetic, intelligent, and hard-working individuals to lead the development of novel causal discovery and machine learning methods, particularly for bioinformatics and computational biology problems, as well as […]
Mens X Machina Probabilistic Graphical Model Toolbox 0.9.3 and Mens X Machina Common Toolbox (previously named Commons Toolbox) 0.9.3 are available for download. The toolboxes were completely rewritten and are mostly object-oriented now. Support for the MMHC algorithm and the junction-tree algorithm for structure learning and inference, respectively, was added. The toolboxes are not compatible […]
Knowledge in the form “A causes B” and “A does not cause B” is often available. For example, in an experiment where temperature (A) is controlled, then for any quantity B that changes we can infer A causes B. Our new publication in ICML shows how to incorporate such knowledge when inducing a causal models […]
Is it possible to predict a disease is correlated with an exposure factor without ever performing a study to measure them? The answer is shown to be yes, in some cases, by analyzing existing datasets that measure these two quantities, but not jointly. The idea is to induce all causal models that are simultaneously consistent […]
The STATegra collaborative FP7 proposal has been accepted for funding by the EC! Our group is a member of the STATegra consortium and will be leading the Work Package related to the development of machine learning, statistical, and data mining methods to integratively analyze heterogeneous biological datasets. STATegra funding will allow us to grow, expand, […]
Can we learn causal relationships from observations? In this 3-hour tutorial we attempt to give the intuition behind causal discovery from observational data, discuss the main assumptions, present the theory of Bayesian networks and some basic causal discovery algorithms, demonstrate some of their most successful applications to feature selection and biomedical data, and also share […]
The management of the Institute of Computer Science, Foundation of Research and Technology, Hellas has recently (Oct. 2010) decided to found the Bioinformatics Laboratory, with the Mens X Machina group members as its founding and core members and Prof. Tsamardinos as its first Head. The decision reflects the commitment of the management to progressing and […]
New versions (0.9.2) of our MATLAB® toolboxes have been released. New features in version 0.9.2 of Mens X Machina Probabilistic Graphical Model Toolbox (MxM PGM) include: Skeleton identification error estimation/calculation utilities Templates for custom functions, handles to which can be used as values of skeleton identification function parameters. New features in version 0.9.2 of Mens […]
New versions (0.9.1) of our MATLAB® toolboxes have been released. The Mens X Machina Bayesian Network Toolbox has been renamed to Probabilistic Graphical Model Toolbox, because we intent to include functionality that covers other types of graphical models such as Maximal Ancestral Graphs (MAGs) and Pairwise Casual Graphs (PCGs) in the future. New features in […]
A new Bioinformatics paper adapts and compares MMPC for molecular signature discovery in high-dimensional, micro-array gene-expression survival data outperforming the state-of-the-art in the field. The source code of the algorithm and experimental scripts are available in the Software section.
We have just released the first versions of our toolboxes for MATLAB®: Mens X Machina Bayesian Network Toolbox aims to provide a comprehensive set of tools for bayesian network inference and structure learning. Currently only bayesian network skeleton learning using the MMPC algorithm is implemented. Support for full structure learning and inference will be added […]
Our latest journal paper entitled Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification has appeared in two parts in the Journal of Machine Learning Research, Special Topic on Causality, vol. 11, 2010 (see Publications).
A paper based on Ms. Sofia Triantafilou’s master thesis, Learning Causal Structure From Overlapping Variable Sets, will be presented at the Thirteenth International Conference on Artificial Intelligence and Statistics which will be held in Chia Laguna Resort, Sardinia, Italy on May 13-15, 2010.
A tutorial on Causal Discovery entitled An Introduction to Causal Discovery will be presented by the group head, Dr. Ioannis Tsamardinos, at The Hellenic Conference on Artificial Intelligence (SETN) 2010, which will be held in Athens, Greece on May 4-7, 2010.
We are very happy that our group’s website has been launched! The website contains information about our group, ourselves and our educational activities, as well as our publications. The software section is going to be populated with more of our software soon.