• Machine Learning Approaches for Biomarker Discovery Using Gene Expression Data 

      Zhang, Xiaokang; Jonassen, Inge; Goksøyr, Anders (Chapter, 2021)
      Biomarkers are of great importance in many fields, such as cancer research, toxicology, diagnosis and treatment of diseases, and to better understand biological response mechanisms to internal or external intervention. ...
    • Machine learning approaches for high-dimensional genome-wide association studies 

      Malik, Muhammad Ammar (Doctoral thesis, 2022-08-24)
      Formålet med Genome-wide association studies (GWAS) er å finne statistiske sammenhenger mellom genetiske varianter og egenskaper av interesser. De genetiske variantene som forklarer mye av variasjonene i genomfattende ...
    • Machine Learning methods for mood disorder decision support 

      Oleksy, Tomasz Artur (Master thesis, 2017-07-11)
    • Macrophage phenotype transitions in a stochastic gene-regulatory network model 

      Frank, Anna-Simone Josefine; Larripa, Kamila; Ryu, Hwayeon; Röblitz, Susanna (Journal article; Peer reviewed, 2023)
      Polarization is the process by which a macrophage cell commits to a phenotype based on external signal stimulation. To know how this process is affected by random fluctuations and events within a cell is of utmost importance ...
    • Macroscale mesenchymal condensation to study cytokine-driven cellular and matrix-related changes during cartilage degradation 

      Weber, Marie-Christin; Fischer, Lisa; Damerau, Alexandra; Ponomarev, Igor; Pfeiffenberger, Moritz; Gaber, Timo; Götschel, Sebastian; Lang, Jens; Röblitz, Susanna; Buttgereit, Frank; Ehrig, Rainald; Lang, Annemarie (Journal article; Peer reviewed, 2020)
      Understanding the pathophysiological processes of cartilage degradation requires adequate model systems to develop therapeutic strategies towards osteoarthritis (OA). Although different in vitro or in vivo models have been ...
    • Making the BKW Algorithm Practical for LWE 

      Budroni, Alessandro; Guo, Qian; Johansson, Thomas; Mårtensson, Erik; Stankovski Wagner, Paul (Journal article; Peer reviewed, 2020)
      The Learning with Errors (LWE) problem is one of the main mathematical foundations of post-quantum cryptography. One of the main groups of algorithms for solving LWE is the Blum-Kalai-Wasserman (BKW) algorithm. This paper ...
    • The male germ cell gene regulator CTCFL is functionally different from CTCF and binds CTCF-like consensus sites in a nucleosome composition-dependent manner 

      Sleutels, Frank; Soochit, Widia; Bartkuhn, Marek; Heath, Helen; Dienstbach, Sven; Bergmaier, Philipp; Franke, Vedran; Rosa-Garrido, Manuel; van de Nobelen, Suzanne; Caesar, Lisa; van der Reijden, Michael I.J.A.; Bryne, Jan Christian; van Ijcken, Wilfred F.J.; Grootegoed, J. Anton; Delgado, M. Dolores; Lenhard, Boris; Renkawitz, Rainer; Grosveld, Frank; Galjart, Niels (Peer reviewed; Journal article, 2012-06-18)
      Background: CTCF is a highly conserved and essential zinc finger protein expressed in virtually all cell types. In conjunction with cohesin, it organizes chromatin into loops, thereby regulating gene expression and epigenetic ...
    • Managing spatial selections with contextual snapshots 

      Mindek, Peter; Gröller, Eduard; Bruckner, Stefan (Peer reviewed; Journal article, 2014-12)
      Spatial selections are a ubiquitous concept in visualization. By localizing particular features, they can be analysed and compared in different views. However, the semantics of such selections often depend on specific ...
    • Market equilibria and money 

      Flåm, Sjur Didrik (Journal article; Peer reviewed, 2021)
      By the first welfare theorem, competitive market equilibria belong to the core and hence are Pareto optimal. Letting money be a commodity, this paper turns these two inclusions around. More precisely, by generalizing the ...
    • MassAnalyzer, a program to help find labeled peptides and compare them to their unlabeled counterparts in a SILAC experiment 

      Narrevik, Tommy (Master thesis, 2008-11-27)
      Mass spectrometry(MS) have become an increasingly popular analysis method for high throughput experiments on proteins in biology. SILAC(stable isotope labeling by amino acids in cell culture) is a method within MS that ...
    • MassSorter: a tool for administrating and analyzing data from mass spectrometry experiments on proteins with known amino acid sequences 

      Barsnes, Harald; Mikalsen, Svein-Ole; Eidhammer, Ingvar (Peer reviewed; Journal article, 2006-01-26)
      Background: Proteomics is the study of the proteome, and is critical to the understanding of cellular processes. Two central and related tasks of proteomics are protein identification and protein characterization. Many ...
    • Mathematical Modeling and Simulation Provides Evidence for New Strategies of Ovarian Stimulation 

      Fischer, Sophie; Ehrig, Rainald; Schäfer, Stefan; Tronci, Enrico; Mancini, Toni; Egli, Marcel; Ille, Fabian; Krüger, Tillmann H. C.; Leeners, Brigitte; Röblitz, Susanna (Journal article; Peer reviewed, 2021)
      New approaches to ovarian stimulation protocols, such as luteal start, random start or double stimulation, allow for flexibility in ovarian stimulation at different phases of the menstrual cycle. It has been proposed that ...
    • Mathematical modelling of follicular growth and ovarian stimulation 

      Fischer-Holzhausen, Sophie; Röblitz, Susanna (Journal article; Peer reviewed, 2022)
      The aim of ovarian stimulation in fertility treatment is to increase the number of large follicles and hence the number of eggs that can be retrieved for in vitro fertilisation (IVF). However, large inter- and intra-individual ...
    • Mathematical modelling of nitric oxide/cyclic GMP/cyclic AMP signalling in platelets 

      Kleppe, Rune; Jonassen, Inge; Doskeland, Stein Ove; Selheim, Frode (Peer reviewed; Journal article, 2018-02-19)
      Platelet activation contributes to normal haemostasis but also to pathologic conditions like stroke and cardiac infarction. Signalling by cGMP and cAMP inhibit platelet activation and are therefore attractive targets for ...
    • A matrix-free method for regularisation with unrestricted variables 

      Fotland, Bjørn Harald (Master thesis, 2008)
      In this thesis a method for the partially norm constrained least squares problem is presented. The method relies on a large-scale trust-region solver and has a low storage requirement. A combination of image misalignment ...
    • A matter of timing : A modelling-based investigation of the dynamic behaviour of reproductive hormones in girls and women 

      Fischer-Holzhausen, Sophie (Doctoral thesis, 2023-05-05)
      Hypothalamus-hypofyse-gonade aksen er en del av det kvinnelige endokrine systemet, og regulerer evnen til reproduksjon. Hormoner produsert og utskilt fra tre kjertler (hypotalamus, hypofysen, eggstokkene) påvirker hverandre ...
    • Maximum matching width: New characterizations and a fast algorithm for dominating set 

      Jeong, Jisu; Sæther, Sigve Hortemo; Telle, Jan Arne (Peer reviewed; Journal article, 2015)
      We give alternative definitions for maximum matching width, e.g., a graph G has mmw(G) <= k if and only if it is a subgraph of a chordal graph H and for every maximal clique X of H there exists A,B,C \subseteq X with A ...
    • Maximum number of edges in graph classes under degree and matching constraints 

      Måland, Erik Kvam (Master thesis, 2015-05-12)
      In extremal graph theory, we ask how large or small a property of a graph can be, when the graph has to satisfy certain constraints. In this thesis, we ask how many edges a graph can have with restrictions on its degree ...
    • Maximum number of objects in graph classes. 

      Hellestø, Marit Kristine Astad (Master thesis, 2015-05-31)
      The focus of this thesis is the study and implementation of two exact exponential time algorihms. These algorihms finds and lists the number of minimal dominating sets and the number of minimal subset feedback vertex sets ...
    • Measures in Visualization Space 

      Bolte, Fabian; Bruckner, Stefan (Chapter, 2020)
      Measurement is an integral part of modern science, providing the fundamental means for evaluation, comparison, and prediction. In the context of visualization, several different types of measures have been proposed, ranging ...