Prof. Tsamardinos is an invited speaker at the Causal Modeling and Machine Learning workshop (CaMaL 2018) that takes place in in Guangzhou, China, on June 8, 2018. He will present his recent work in “Logic-based Causal Discovery and other advances”
Την Τετάρτη 16/5 ο καθηγητής κ. Τσαμαρδίνος Ιωάννης θα πραγματοποιήσει παρουσίαση με θέμα:” Η αξιοποίηση των δεδομένων στις επιχειρήσεις”. Η ομιλία θα πραγματοποιηθεί στο πλαίσιο της εκδήλωσης που διοργανώνει το Πανεπιστήμιο Κρήτης, η Περιφέρεια Κρήτης και το Εμπορικό και Βιομηχανικό Επιμελητήριο Ηρακλείου με θέμα: “Πανεπιστήμιο-Καινοτομία-Επιχειρηματικότητα”. Η Εκδήλωση θα πραγματοποιηθεί την Τετάρτη 16/5 και ώρα 18:00 […]
The HUNT Lung Cancer Model Risk Calculator is an online tool, developed in conjunction with MXM researchers, which allows to assess the individual risk of developing lung cancer in smokers of all ages. The scientific study describing the tool was published in the EBioMedicine journal (link), while the tool is available here. We are glad […]
MXM contributed in creating a precise tool for evaluating the personal risk of developing lung cancer in smokers. The tool is based on a mathematical model, namely the “HUNT Lung Cancer Model”, which accepts seven different clinical parameters and computes the probability of developing lung cancer within 6 and 16 years. Several characteristics make this […]
Suicide prevention in mental health patients is a complex, important tasks carried on by dedicated physicians and nurses. Correctly evaluating the individual risk of suicide is of paramount importance. MXM personnel is participating in a common project with the University of Huddersfield for creating mathematical models able to evaluate the risk of committing suicide in […]
Professor Tsamardinos is invited speaker to the “Advanced Data Analytics Seminar Series” organized by the “Data Science Institute” Of University of Manchester. He will present his work on “Automating predictive modelling and knowledge discovery”. The seminar will take place on 24th of April.
After several successful recruitments over the past year, the MensXMachina (MXM) research group is pleased to announce several calls for Graduate students, Research Scientists and Software Developers/Engineers. The successful candidates will join recently funded International and Domestic projects on Cancer Research, Biomedicine, IoTs and others. In this call we are looking for Researchers with a strong […]
Professor Tsamardinos will participate in the first “TEDxUniversityOfCrete” event on the 24th of March. His talk about Technology destinations, will pose a variety of questions about its applications and its role.
We developed new approaches for co-analyzing categorical and continuous data in causal discovery algorithms. Specifically, we devised new conditional independence tests for mixed data that can be directly embedded in constraint-based algorithms like PC and FCI. Check out the open-access paper or the readcube version
MXM new work adapts constraint-based, feature selection algorithm to data that are measured at multiple time points. This approach can be used, for example, to identify the genes whose expression over time has a trajectory highly predictive for a given disease. Check out the paper at the BMC Bioinformatics website (link) and the implementation in […]
Two posters co-authored by MXM researchers were displayed at the World Conference on Lung Cancer 2017, held in Yokohama, Japan, from the 15th to the 18th of October. The first poster illustrates a new stratification model for identifying subjects at high risk of developing lung cancer, and that should undergo further clinical assessment. Our second […]
Prof. Ioannis Tsamardinos gave a keynote lecture at The 12th Conference of the Hellenic Society for Computational Biology and Bioinformatics (11-13 October, 2017, Athens, Greece). The subject of the lecture is Automating predictive modelling and knowledge discovery for biomedical application. Find out more at the conference website: HSCBB17
The 10th Conference of Hellenic Bioinformatics just finished, and member of the MXM laboratory have presented several works and posters. Have a look to the program here: https://hscbio.wordpress.com/conferences-when/2017-2/ Presentations: “Reconstructing Ikaros Regulatory Network by Applying Causal Discovery Methods on a Compendium of Gene Expression Profiles from Acute Lymphoblastic Leukemia Patient” Authors: Maria Nikoloudaki, Vincenzo Lagani, […]
For the second time in three years the MASSCAUSAL workshop was held in Crete, Greece, co-funded by the University of Crete, University of Amsterdam and the European Research Council (ERC). From the 1st to the 3rd of September 2017 experts in Causal Discovery and Mass / Flow Cytometry met together for discussing the latest developments […]
The Statistically Equivalent Signatures (SES) algorithm was published today on the Journal of Statistical Software: https://www.jstatsoft.org/article/view/v080i07 The SES algorithm allows to identify multiple sets of predictors, all of which have equivalent predictive power and minimal number of elements. SES is implemented in the R MXM package, freely available on CRAN: https://cran.r-project.org/web/packages/MXM/index.html
Our project CAUSALPATH now features on the current issue of Eur13! Read about the objectives and the progresses of our activities in the online magazine: Online magazine Jump to page 17 if you are impatient to read about CAUSALPATH
Prof Tsamardinos will present two new scientific works at The 2017 ACM SIGKDD Workshop on Causal Discovery, Halifax, Nova Scotia, Canada, Aug 14, 2017 – Aug 14, 2017: Tsagris M., Borboudakis G., Lagani V. and Tsamardinos I. (2017). Constraint-based Causal Discovery with Mixed Data. 2017 ACM SIGKDD Workshop on Causal Discovery. And Tsirlis K., Lagani […]
Prof. Tsamardinos’s invited talk at the 2nd international congress “Evolution and Cancer Prof. Tsamardinos gave an invited talk at the 2nd international congress “ Evolution and Cancer” in Thessaloniki on the June 30th. Link: https://www.youtube.com/watch?v=EVtMeZixRbg#t=5h14m12s
Dr. Tsagris gave an invited talk at the 2017 Annual Meeting of the Statistical Society of Canada (University of Manitoba, Winnipeg, June 11-14). The title of the talk is “A Dirichlet Regression Model for Compositional Data with Zeros” Abastract: Compositional data are met in many different fields, such as economics, archaeometry, ecology, geology and political […]
Dr. Maria Markaki and Prof Tsamardinos participated in a new paper published on Scientific Report. In this work an advanced machine-learning pipeline, namely Just Add Data Bio (JADBio) is used for deriving MatureP, a classifier able to predict secreted proteins from information from their mature regions. Check it online: link to paper
On the 14th of August 2017 Prof. Tsamardinos will give an invited talk at the 2017 ACM SIGKDD Workshop on Causal Discovery. Title: “Advances in Causal-Based Feature Selection” The talk will illustrate the past and explore the future of feature selection algorithms based on Causal Discovery theory. Link to the conference Abstract: Feature selection (a.k.a. […]
Gnosis Data Analysis, a University of Crete spin-off, is currently looking for a scientific programmer, a data analyst, and a developer with experience in artificial intelligence. Check out the announcements at http://www.gnosisda.gr/careers/
Our on-line service SCENERY is now featured in a new publication on Nucleic Acid Research. SCENERY allows researcher to apply (causal) network reconstruction methods to flow and mass cytometry data, in order to identify putative interactions across measured quantities (e.g., proteins). SCENERY can be accessed at scenery.csd.uoc.gr, while the new publication can be read here
With great pleasure we announce the second International Workshop on Computational methods for single-cell data. The event is invitation-only and is jointly hosted by the University of Crete in collaboration with the Karolinska Institutet and the University of Amsterdam under the aegis of the European Research Council (ERC). [see link]
On the 12th of May Dr. George Arabatzis, ETH-Zurich, will give the talk “Bayesian Uncertainty Quantification: Applications in Pharmacodynamics and Molecular Dynamics”. Time and place: 12:00 in room n. H204 (CSD building). Host: Dr. Yannis Pantazis.
Prof. Tsamardinos will give an invited talk during the 2nd international congress “Evolution and Cancer: Cancer across life. The congress will be held in the Vlatades monastery, Thessaloniki from the 29th June to 1st of July 2017 Title of the talk: “From human to artificial intelligence, to artificial intelligence for cancer research”
Prof. Tsamardinos gave an invited talk at the DALI 2017 meeting, held in Tenerife, Canary Islands, 18-20/4/2017. His talk focused on applying causal analysis on a complex biological problem, showing how the idiosyncrasies of real-world tasks can drive the development of new causal algorithms and approaches. Title: Causal Inference from Single Cell, Mass Cytometry Data: an Integrative […]
The SciLife facility (Stockholm, Sweden) processed our biological samples and the data are now under preparation and quality checking. This CyTOF dataset will allow to identify the effect of TGFB1 and TGFB3 on CD4+ immune cells, using the causal discovery methods developed in CAUSALPATH
On March 28, Yannis Pantazis, PhD, gave an invited talk at the Scaling Cascade in Complex Systems workshop held at the Free University of Berlin. The title of the talk is “Information-theoretic Uncertainty and Sensitivity Bounds for Stochastic Dynamics and Rare Events“. More info at: https://conference.imp.fu-berlin.de/sfb1114-sccs-2017/program/ms#MS8
The preprint version of our new publication is now available on bioRxiv. This work applies two distinct causal discoveries methods on mass-cytometry (CyTOF) data, producing causal findings that are reproducible across two independent studies. Check the full text here: https://t.co/JmW59B3nmt
Following our annual tradition we celebrated the coming of the new year by “cutting” the cake, better known as Vasilopita.(https://en.wikipedia.org/wiki/Vasilopita). This year, Klio was lucky one ! Happy New Year MxMers!
Prof. Tsamardinos attended the Thirtieth Annual Conference on Neural Information Processing Systems (NIPS), held at the Centre Convencions Internacional Barcelona, 5-10 December 2016. https://nips.cc/Conferences/2016
Prof. Tsamardinos visited Athens during 24-25 of November and gave two invited talks about his scientific work. The first one was held on the 24th of November, about: “Advances in Feature Selection in Data Analytics”, at the Department of Digital Systems of University of Piraeus and the second one on the 25th of November about:” Logic-Based […]
Job description We are looking for an enthusiastic, highly motivated software developer with a strong background in full-stack web applications to join our team and be the lead programmer for our data analysis web platform. The platform will host applications on the cloud providing data analytics solutions for researchers and practitioners across disciplines. As a software developer, you […]
Prof. Ioannis Tsamardinos gave a Distinguished Lecture on August 19th about: “Logic-Based Causal Discovery for Heterogeneous Datasets,” as part of the Distinguish Lecture Series organized by “Center for Causal Discovery”, University of Pittsburgh, Carnegie Mellon University, Pittsburgh Supercomputing Center and Yale University.
On the 26th of August 2016 Prof. Ioannis Tsamardinos introduces the novel field of Logic-based Integrative Causal Discovery in an invited lecture at the North Carolina State University, host Prof. Yannis Viniotis Link to the talk: video
Our post doc, Sofia Triantafillou, gave a tutorial on integrative, logic-based causal discovery in the prestigious conference “Uncertainty in Artificial Intelligence” (UAI 2016, July 25-29, NY). Take a look at the slides here (link), or wait until the video is available on UAI’ s webpage: http://www.auai.org/uai2016/tutorials.php
Prof. Tsamardinos talk at LINCS (Laboratory of Information, Networking and Communication Sciences), Paris, France 24/02/2016. Link to the video Abstract: Computational Causal Discovery aims to induce causal models,causal networks, and causal relations from observational data withoutperforming or by performing only few interventions (perbutations,manipulations) of a system. While predictive analytics create models thatpredict customer behavior for […]
Giorgos Athineou, MSc student at the Computer Science Department, UOC and member of MXM group presented the paper “SCENERY: a Web-Based Application for Network Reconstruction and Visualization of Cytometry Data.” on the 10th International Conference on Practical Applications of Computational Biology & Bioinformatics that took place in Seville Spain 1-3 of June 2016.
The ETIO algorithm is a innovative causal analysis method that allows identifying causal relationships by integrating several datasets obtained under different experimental conditions. The algorithm will be presented in the prestigious ACM SIGKDD Conference on Knowledge Discovering and Data Mining (KDD 2016, 13 – 17 August). KDD is an international event that brings together the top-players in […]
Prof. Tsamardinos will present recent developments in logic-based causal discovery, based on the latest JMLR paper with Sofia Triantafillou: “Constraint-based Causal Discovery from Multiple Interventions over Overlapping Variable Sets” during the 9th Hellenic Conference on Artificial Intelligence held in Grand Hotel Palace Thessaloniki, 18-20 May 2016.
Robin Mjelle, Ph.D. and researcher at the Norwegian University of Science and Technology, was awarded a first-time foundation grant of $300,000 for his innovative work in the identification of biomarkers for the early detection of lung cancer. The grant was assigned by the Bonnie J. Addario Lung Cancer Foundation (ALCF) and the International Association for the Study of Lung Cancer (IASLC). These […]
Prof. Ioannis Tsamardinos and Dr. Vincenzo Lagani will give an invited talk on “Signature discovery in multi–omics datasets, novel tools” at the 1st International NTNU Symposium on Current and Future Clinical Biomarkers of Cancer, to be held in Trondheim, Norway, June 16th – 17th. Check the symposium website for more information
Prof. Tsamardinos will present the field of logic-based integrative causal discovery during two different talks to be held in Paris, France, in the upcoming week. The talks will illustrate the characteristics of a new, logic-based approach to causal discovery, that has been partly pioneered by our group. This approach is more robust to statistical errors, makes more […]
ELIXIR is an inter-governmental organisation which builds on existing data resources and services within Europe. Its main objective is orchestrating the collection, quality control and archiving of large amounts of biological data produced by life science experiments. Prof. Tsamardinos will give an invited talk at the forthcoming meeting “In silico infrastructures for Life Science’s Big Data – and the […]
Our new web site is on-line! Check it out: www.mensxmachina.org
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: […]