Digitization of society means that we can collect ever-increasing amounts of data from different sources. This means that Big Data and various methods linked to AI (Artificial Intelligence) are becoming an increasingly important part of our work in agricultural sciences and genetics. For data to be meaningful, it is important that they accurately reflect reality and also that our analysis models meet transparency and reproducibility requirements. My research is therefore largely focused on creating efficient data collection systems and ensuring that data is handled in a validated and traceable way. In this way, we make it possible to translate advanced theoretical models into useful applications that can contribute to better knowledge in genetics and breed animals adapted to modern production systems and a changing environment. Right now, my research is being conducted within two projects, Gigacow and Defend2020.
I am giving some lectures on the course Bioinformatics 15 HP but am currently working mainly on contributing to the Galaxy Training Network which is an open resource for learning bioinformatics with the help of Galaxy.
Gigacow is SLU's investment in large-scale data collection from dairy farms. It is a university-wide resource that can also be used by external researchers. As coordinator, my job is to capture as many measurable characteristics (phenotypes) as possible from the cows on the farms participating in the network. We then supplement these measurements with genetic information from each animal as well as other information about the farms in order to better understand the interaction between animals, humans and production methods. My own research focus is on exploring the genetic characteristics of crosses and the potential for increasing animal health, productivity and resource efficiency on our cows. An important part of the work in Gigacow is to to collaborate with other parties in order to support work on technology and method development where our platform makes Gigacow a natural test bed for new sensors and machines. Method development is also an important part of genetics where both machines that analyze genetic material and the software that analyzes data are constantly being developed.
Defend2020 is an EU project in which we collaborate with researchers in Europe and Africa to stop the spread of Lumpy Skin Disease and African swine fever. In the project, SLU is responsible for the study of the interaction between viruses and host animals in order to better manage and fight the two viruses. An important part of the work is also to ensure that the tools produced by the project can be used by researchers and veterinarians all over the world. In Defend2020 we therefore use a platform called Galaxy in order to create reproducible workflows used to support data analys and training of stakeholders working to combat the dual threat of Lumpy Skin Disease and African swine fever. During the outbreak of Covid-19, other members of the Galaxy team have built up a platform for data analysis of Covid-19 worldwide and the goal is that we can use the same technical platform for other diseases as well.
I mainly focus on three areas in my work to advance our capability to use large scale phenotyping and genotyping in agricultural sciences.
1. Development of better tools for large-scale measurement of animal characteristics.
2. Improving the quality of reference genomes and other resources to study genetic diversity in different (cow) breeds.
3. Better tools for reusing and sharing analytics flows used to analyze data.
By integrating new measurement methods with effective data analysis support, we can increase knowledge in both genetics and agricultural science. This requires close collaboration between farmers, geneticists and specialists in computer science, biotechnology and bioinformatics. To achieve this, I use Galaxy as a data management and analysis platform to share and develop the work we do linked to genetics, Gigacow and Defend2020.
As coordinator for Gigacow , I depend on close cooperation with both the dairy farmers of the network and the organizations with which they work. In addition to SLU's own network, contacts via Växa Sweden, AgroÖst and Vreta Cluster have been an important part of the infrastructure development. Right now, my goal is to go out and meet our farmers either on the farms or in conjunction with agricultural days and other meetings.
Gigacow is also active in developing new technology and applying it. We are members of the Nordic Testbed Network, which works to support digital development and participate in projects that increase our ability to collect and provide data. The development of new methods in genetics also plays an important role and we therefore collaborate with the National Genomics Infrastructure of Sweden at the SciLife lab, which is one of the world's leading DNA sequencing infrastructures with new technologies such as Oxford Nanopore Technology and Single Molecule, Real Time sequencing, which creates new opportunities to better map the genome of both our cows and the microorganisms that live in or around them.
With globalization and climate change, international knowledge exchange plays an important role in meeting increasing challenges such as drought, floods and animal diseases. Via SLU Global and various joint projects, we work closely with many other countries and since I started working at SLU I have visited about 30 different countries on three different continents. In addition to the Defend2020 and Galaxy project, I am currently working primarily in Nordic collaborations funded by the Nordic Joint Committee for Agricultural and Food Research and in collaboration with African colleagues at the International Livestock Research Institute in Kenya & Ethiopia and the Agricultural Research Council in South Africa. The goal is that, with the help of new reference genomes and improved data collection, we will be able to transfer both knowledge and methods between the different countries. A small travel report focusing on how Galaxy and bioinformatics can contribute to agricultural research in global partnerships is available here .
If you are interested in any of my projects or something else in the borderland between genetics, bioinformatics and technology development, you can only contact me by e-mail (firstname.lastname@example.org), whether you are a farmer, researcher, student or have a different background .
I got a masters degree in molecular biotechnology, engineering and from the beginning my goal was to focus on biotechnology but supplement it with knowledge in bioinformatics in order to have a comprehensive picture of the research chain from sampling to results. Thanks to Professor Jan Komorowski at the Linnaeus Center for Bioinformatics, I got the chance to do a research internship with Dr Dariusz Plewczynski at the University of Warsaw focusing on protein interactions and structural biology. The work there was the start of my interest in data quality and large-scale data collection when I realized that new, more efficient algorithms in machine learning were secondary to the need for access to quality-assured data that could be used as training datasets for future machine learning applications. My work in Poland also helped me get Anders Wall's scholarship to Young Researchers which provided me with the funds and resources to shift my research focus from biotechnology to working more with applied bioinformatics.
I did my PhD at what is today the SLU Global Bioinformatics Center with Professor Erik Bongcam-Rudloff as the main supervisor. What initially interested me was his work with the eBiokit, which is a portable platform for education and basic data analysis which is well suited for work in low or middle income countries. As a doctoral student, I initially worked with the Molecular Methods database, which was a project within the Biobank and Biomolecular Research Infrastructure of Sweden (BBMRI.se) to minimize the influence of pre-analytical variables caused by inadequate documentation and differences in method selection in different laboratories. During the doctoral period, funding for BBMRI.se was stopped by the Swedish Research Council but fortunately I was also working in the team that wrote the grant application for B3Africa, which was a project where we combined eBiokit with other IT solutions to create a platform for data-integrated biobanks in low and middle-income countries. The result was that my doctoral thesis got a focus on the entire chain from sample collection to data analysis and also the legal barriers that often limit data collection and data sharing. This was also the start of my involvement in the Galaxy project as we used the platform to help researchers in medicine and biology to quickly access best practice methods to perform reproducible data analysis using different bioinformatics tools.
I am currently employed at the Section of Quantitative Genetics working with the Gigacow and Defend2020 with professor Dirk-Jan de Koning as the PI at SLU. Apart from the research on high-throughput phenotyping and work on genetics research we also reuse many of the conclusions we have drawn in B3Africa with the long-term goal to contribute to the harmonization of how we work with bioinformatics in animal genetics to maximize the exchange between different countries for genetics research and genetic evaluations.
I am currently co-supervising one doctoral student, Renaud van Damme at the SLU Global Bioinformatics Center and I also supervise various degree projects at the bachelor's and master's level when appropriate.
In order to draw attention to the Molecular Methods database, we started a collaboration with the journal Biorpreservation & Biobanking where I served as a guest editor for a special section on biobanking for developing countries and methods were shared via the Molecular Methods database . The contacts and experiences from that work together with Erik Bongcam-Rudloff's previous work with the eBiokit  gave us the opportunity to put together the B3Africa project  where I designed and was responsible for the work to create a user-friendly platform for bioinformatics that would be integrated with other provincial and data collection modules.
The work and lessons I drew from the two projects are described in my doctoral dissertation , which is the basis for how we have now chosen to develop the data management and analysis component of Gigacow and also how i have shaped my research agenda for the future  with a focus on data collection and more efficient data analysis with help of Galaxy 
 Klingström, T. (2013) 'Biobanking in Emerging Countries', Biopreservation and Biobanking, vol. 11, no. 6, pp. 329-330. DOI: 10.1089 / bio.2013.1161.
 Hernandez-de-Diego, R., de Villiers, EP, Klingström, T., Gourlé, H., Conesa, A. and Bongcam-Rudloff, E. (2017) 'The eBioKit, a stand-alone educational platform for bioinformatics', Ouellette, F. (ed), PLOS Computational Biology, vol. 13, no. 9, pp. E1005616. DOI: 10.1371 / journal.pcbi.1005616.
 Klingstrom, T., Mendy, M., Meunier, D., Berger, A., Reichel, J., Christoffels, A., Bendou, H., Swanepoel, C., Smit, L., Mckellar, Basset, C., Bongcam-Rudloff, E., Soderberg, J., Merino-Martinez, R., Amatya, S., Kihara, A., Kemp, S., Reihs, R. and Muller, H. (2016 ) 'Supporting the development of biobanks in low and medium income countries', IEEE, pp. 1-10. DOI: 10.1109 / ISTAFRICA.2016.7530672. (Open access version of paper in PhD thesis)
 Klingström, T. (2017) 'Data integration and handling', Uppsala, Swedish University of Agricultural Sciences. Acta Universitatis agriculturae Sueciae, 1652-6880; 2017 99th Available at https://pub.epsilon.slu.se/14669/.
 Klingstrom, T., Bongcam-Rudloff, E. and Vinnere Pettersson, O. (2018) 'A comprehensive model of DNA fragmentation for the preservation of High Molecular Weight DNA', bioRxiv 254276; DOI: 10.1101 / 254276.
 Fallmann, J., Videm, P., Bagnacani, A., Batut, B., Doyle, M.A., Klingstrom, T., Eggenhofer, F., Stadler, P.F., Backofen, R. and Grüning, B. (2019) 'The RNA workbench 2.0: next generation RNA data analysis', Nucleic Acids Research, vol. 47, no. W1, pp. W511 – W515 [Online]. DOI: 10.1093 / nar / gkz353.