Computational Data Science Laboratory at University of Granada

1. Brief description of the institution:

The University of Granada (UGR) was founded in 1531 and is one of the largest and most important universities in Spain. With over 51,000 undergraduate and postgraduate students and almost 3,000 members of staff, the UGR offers over 90 undergraduate degrees, 160 master’s degrees (8 of which are international double degrees) and 28 doctoral programs via its 124 departments and nearly 50 centers. Accordingly, the UGR offers one of the most extensive and diverse ranges of higher education programs in Spain.

The UGR has been awarded with the "Human Resources Excellence in Research (HRS4R)", which reflects the institution’s commitment to continuously improving its human resource policies in line with the European Charter for Researchers and the Code of Conduct for the Recruitment of Researchers. The UGR is also internationally renowned for its excellence in diverse research fields and ranked among the top Spanish universities in a variety of ranking criteria, such as national R&D projects, fellowships awarded, publications, and international funding.

The UGR is one of the few Spanish Universities listed in the Shanghai Top 500 ranking - Academic Ranking of World Universities (ARWU). The 2022 edition of the ARWU places the UGR in 201-300th position in the world and as the 2-5 highest ranked universities in Spain (http://sl.ugr.es/0d7D),,) reaffirming its position as an institution at the forefront of national and international research. The UGR stands out in the specialties of Library & Information Science (position 38); Food Science & Technology (30) and Hospitality & Tourism Management (51-75), according to the latest edition of this prestigious ranking by specialties (http://sl.ugr.es/0bSp)..) A little lower in the ranking, the UGR also stands out in Mathematics (76-100).

Additionally, the UGR has 9 researchers who are at the top of the Highly Cited Researchers (HCR) list (http://sl.ugr.es/0d7E),,) most of these related to the area of Computer Science. It is also well recognized for its web presence (http://sl.ugr.es/0a6i),,) being positioned at 42th place in the top 200 Universities in Europe.

Internationally, the University of Granada is firmly committed to its participation in the calls of the Framework Programme of the European Union. For the duration of the last Framework Programme, Horizon 2020, the UGR obtained a total 120 projects with a total funding of around 29,4 million euros. For the current Framework Programme, Horizon Europe, the UGR has obtained 38 projects, so far, with total funding around 11 € million.

2. Brief description of the Centre/Research Group:

The Computational Data Science Laboratory (the CoDaS Lab) is a research group created in 2022 at the University of Granada. Our research interests include interpretable data science, machine learning and inferential statistics with multivariate techniques applied to data of very different nature: computational biology, analytical chemistry, communication networks, health, and ecology, among others. We specialize in extracting knowledge from complex data and the design of new algorithms and software tools to do so.

Our core strength is the development of fully interpretable tools for deep data understanding. We develop our own models, algorithms, and software for inference and machine learning on multimodal data, with a strong focus on omics data and cancer studies. We have recently developed new inference tools that excel in patient stratification and biomarker discovery for personalized diagnosis and treatment, and extended them for spatial omics analyses.

We provide:

- Techniques, software tools and computer servers for data analysis, design of experiments, sample size computation, patient stratification, interpretation of results, identification of biomarkers, estimation of statistical significance and other similar capabilities for the treatment of omics or other form of complex data.

- The ability to use state-of-the-art multivariate tools for the analysis of complex data: PCA/PLS-DA, sparse methods, variable selection, ASCA, PERMANOVA, Design of Experiments, etc.

- The ability to design new data analysis algorithms tailored to the analysis problem at hand for visualization, anomaly detection, classification, prediction, and optimization.

- The statistical design of clinical/experimental studies, analysis of samples and interpretation of data.

3. Brief description of the Start-Up:

The CoDaS Lab transfers its technology though Datharsis (datharsis.com), see also https://www.b2match.com/e/online-matchmaking-eppermed-ritc26/participants/3328484