A5025629360- Spaceflight effects on biology
- T-cell and B-cell Immunology
- Metabolomics and Mass Spectrometry Studies
- Genomics and Chromatin Dynamics
- RNA and protein synthesis mechanisms
- Cancer Cells and Metastasis
- Muscle Physiology and Disorders
- Genetics, Aging, and Longevity in Model Organisms
- Immune Cell Function and Interaction
- Gene expression and cancer classification
- Epigenetics and DNA Methylation
- Bioinformatics and Genomic Networks
- vaccines and immunoinformatics approaches
- Protein Structure and Dynamics
- Cell Image Analysis Techniques
- Monoclonal and Polyclonal Antibodies Research
- Neuroscience and Neuropharmacology Research
- Single-cell and spatial transcriptomics
- Neuroinflammation and Neurodegeneration Mechanisms
- Immunotherapy and Immune Responses
- Machine Learning in Bioinformatics
- Maternal and fetal healthcare
- scientometrics and bibliometrics research
- Fractal and DNA sequence analysis
- Research Data Management Practices
University of Copenhagen
2018-2024
Genmab (Denmark)
2024
University of Oxford
2015-2023
Harvard University
2023
Lundbeck (Denmark)
2021
Science Oxford
2017
Medawar Building for Pathogen Research
2015
Abstract Epilepsy is one of the most common neurological disorders, yet its pathophysiology poorly understood due to high complexity affected neuronal circuits. To identify dysfunctional subtypes underlying seizure activity in human brain, we have performed single-nucleus transcriptomics analysis >110,000 transcriptomes derived from temporal cortex samples multiple lobe epilepsy and non-epileptic subjects. We found that largest transcriptomic changes occur distinct several families...
Abstract Motivation The identification of predictive biomarker signatures from omics and multi-omics data for clinical applications is an active area research. Recent developments in assay technologies machine learning (ML) methods have led to significant improvements performance. However, most high-performing ML suffer complex architectures lack interpretability. Results We present the application a novel symbolic-regression-based algorithm, QLattice, on selection datasets. This approach...
The interaction between T-cell receptors (TCRs) and major histocompatibility complex (MHC)-bound epitopes is one of the most important processes in adaptive human immune response. Several hypotheses on TCR triggering have been proposed. Many them involve structural dynamical adjustments TCR/peptide/MHC interface. Molecular Dynamics (MD) simulations are a computational technique that used to investigate dynamics at atomic resolution. Such improve understanding signalling level. Here we review...
Abstract Background Spaceflight poses a unique set of challenges to humans and the hostile spaceflight environment can induce wide range increased health risks, including dermatological issues. The biology driving frequency skin issues in astronauts is currently not well understood. Methods To address this issue, we used systems approach utilizing NASA’s Open Science Data Repository (OSDR) on space flown murine transcriptomic datasets focused skin, biochemical profiles 50 NASA human...
Abstract Normal breast luminal epithelial progenitors have been implicated as cell of origin in basal-like cancer, but their anatomical localization remains understudied. Here, we combine collection under the microscope organoids from reduction mammoplasties and single-cell mRNA sequencing (scRNA-seq) FACS-sorted cells with multicolor imaging to profile ducts terminal duct lobular units (TDLUs) compare them cancer subtypes. Unsupervised clustering reveals eleven distinct clusters a...
The naïve human antibody repertoire has theoretical access to an estimated > 10
<title>Abstract</title> <bold>Purpose</bold> This study aims to train a novel explainable machine learning method (QLattice) predict successful vaginal birth after cesarean and compare the performance of these models with other known learning- logistic regression models. <bold>Methods</bold> A Danish cohort including 11 017 women prior giving during year 2004–2016 was used evaluate three algorithms (LASSO, Random Forest, QLattice). Grobmans model as baseline. Two were developed (antenatal...
Abstract Neuroserpin is a serine‐protease inhibitor mainly expressed in the CNS and involved inhibition of proteolytic cascade. Animal models confirmed its neuroprotective role perinatal hypoxia‐ischaemia adult stroke. Although neuroserpin may be potential therapeutic target treatment aforementioned conditions, there still no information literature on distribution during human brain development. The present study provides detailed description changing spatiotemporal patterns focusing...
Abstract The adverse effects of microgravity exposure on mammalian physiology during spaceflight necessitate a deep understanding the underlying mechanisms to develop effective countermeasures. One such concern is muscle atrophy, which partly attributed dysregulation calcium levels due abnormalities in SERCA pump functioning. To identify potential biomarkers for this condition, multi-omics data and physiological available NASA Open Science Data Repository (osdr.nasa.gov) were used, machine...
Abstract Motivation: The binding between a peptide and major histocompatibility complex (MHC) is one of the most important processes for induction an adaptive immune response. Many algorithms have been developed to predict peptide/MHC (pMHC) binding. However, no approach has yet able give structural insight into how peptides detach from MHC. Results: In this study, we used combination coarse graining, hierarchical natural move Monte Carlo stochastic conformational optimization explore...
Abstract Single-cell RNA-seq methods are being increasingly applied in complex study designs, which involve measurements of many samples, commonly spanning multiple individuals, conditions, or tissue compartments. Joint analysis such extensive, and often heterogeneous, sample collections requires a way identifying tracking recurrent cell subpopulations across the entire collection. Here we describe flexible approach, called Conos (Clustering On Network Of Samples), that relies on plausible...
Spaceflight poses a unique set of challenges to humans and the hostile environment can induce wide range increased health risks, including dermatological issues. The biology driving frequency skin issues in astronauts is currently not well understood. To address this issue, we used systems approach utilizing NASA's Open Science Data Repository (OSDR) on spaceflown murine transcriptomic datasets focused skin, biomedical profiles from fifty NASA astronauts, confirmation via data JAXA Twins...
Migraine is a common, polygenic disorder that characterized by moderate to severe headache attacks. attacks are commonly treated with triptans, i.e. serotonin receptor agonists. However, triptans effective in ~ 60% of the population, and mechanisms debated. Here, we aim expose triptan using metabolomics transcriptomics spontaneous migraine We collected temporal multi-omics profiles on 24 patients, samples at attack, 2 h after treatment triptan, when headache-free, cold-pressor test....
Abstract Midbrain dopamine neurons (DNs) respond to a first exposure addictive drugs and play key roles in chronic drug usage 1–3 . As the synaptic transcriptional changes that follow an acute cocaine are mostly resolved within few days 4,5 , molecular encode long-term cellular memory of DNs remain unknown. To investigate whether single induces 3D genome structure DNs, we applied Genome Architecture Mapping nucleus transcriptomic analyses mouse midbrain. We found extensive rewiring...
Abstract A better understanding of the biological factors underlying antidepressant treatment in patients with major depressive disorder (MDD) is needed. We perform gene expression analyses and explore sources variability peripheral blood related to response suffering from recurrent MDD at baseline after 8 weeks treatment. The study includes 281 patients, which were randomized vortioxetine ( N = 184) or placebo 97). To our knowledge, this largest dataset including both placebo-controlled...
Simulating the functional motions of biomolecular systems requires large computational resources. We introduce a computationally inexpensive protocol for systematic testing hypotheses regarding dynamic behavior proteins and nucleic acids. The is based on natural move Monte Carlo, highly efficient conformational sampling method with built-in customization capabilities that allows researchers to design perform number simulations investigate in biological systems. demonstrate use this both...
The code together with examples and tutorials are available from http://www.cs.ox.ac.uk/mosaics.peter.minary@cs.ox.ac.uk.Supplementary data at Bioinformatics online.
Results from randomized controlled trials indicate that no single diet performs better than other for all people living with obesity. Regardless of the plan, there is always large inter-individual variability in weight changes, some individuals losing and not or even gaining weight. This raises possibility that, different individuals, optimal successful loss may differ. The current study utilized machine learning to build a predictive model subjects overweight obesity on New Nordic Diet...