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1. Natural History of Subclinical Atrial Fibrillation Detected by Implanted Loop Recorders
by Diederichsen, Søren Zöga and Haugan, Ketil Jørgen and Brandes, Axel and Lanng, Mathias Buus and Graff, Claus and Krieger, Derk and Kronborg, Christian and Holst, Anders Gaarsdal and Køber, Lars and Højberg, Søren and Svendsen, Jesper Hastrup
Journal of the American College of Cardiology, ISSN 0735-1097, 12/2019, Volume 74, Issue 22, pp. 2771 - 2781
symptoms | continuous monitoring | heart rate | atrial fibrillation progression | atrial fibrillation burden | Cardiac & Cardiovascular Systems | Life Sciences & Biomedicine | Cardiovascular System & Cardiology | Science & Technology | Reproducibility of Results | Electrocardiography, Ambulatory - instrumentation | Follow-Up Studies | Humans | Male | Electrodes, Implanted | Atrial Fibrillation - physiopathology | Equipment Design | Disease Progression | Time Factors | Heart Rate - physiology | Female | Aged | Retrospective Studies | Atrial Fibrillation - diagnosis | Heart failure | Hypertension | EKG | Brain natriuretic peptide | Cardiac arrhythmia | Stroke | Echocardiography | Diabetes mellitus | Health risks | Rhythm | Population studies | Patients | Heart rate | Studies | Variables | Sinuses | Fibrillation | Data collection | Blood pressure | Diabetes | Heart diseases | Monitoring
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2. Full Text Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification
by Andreatta, Massimo and Karosiene, Edita and Rasmussen, Michael and Stryhn, Anette and Buus, Søren and Nielsen, Morten
Immunogenetics (New York), ISSN 0093-7711, 11/2015, Volume 67, Issue 11, pp. 641 - 650
Human Genetics | Gene Function | Allergology | Biomedicine | Immunology | Peptide binding | Artificial neural networks | T cell cross-reactivity | Binding core | MHC class II | Peptide-MHC | Cell Biology | Genetics & Heredity | Life Sciences & Biomedicine | Science & Technology | Amino Acid Sequence | Computational Biology - methods | Peptide Fragments - metabolism | Humans | Models, Molecular | Molecular Sequence Data | Histocompatibility Antigens Class II - chemistry | Epitopes - immunology | Sequence Homology, Amino Acid | Peptide Fragments - chemistry | Algorithms | Animals | Histocompatibility Antigens Class II - immunology | Databases, Protein | Protein Binding | Histocompatibility Antigens Class II - metabolism | Mice | Binding Sites | Cluster Analysis | Neural Networks (Computer) | Chemical properties | Peptides | T cells | Neural networks | Analysis | Antigenic determinants | Index Medicus | Tcell cross-reactivity
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3. Full Text NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11
by Lundegaard, Claus and Lamberth, Kasper and Harndahl, Mikkel and Buus, Søren and Lund, Ole and Nielsen, Morten
Nucleic acids research, ISSN 0305-1048, 7/2008, Volume 36, Issue suppl_2, pp. W509 - W512
Life Sciences & Biomedicine | Biochemistry & Molecular Biology | Science & Technology | Peptides - chemistry | Humans | Peptides - immunology | Histocompatibility Antigens Class I - genetics | HLA Antigens - genetics | HLA Antigens - metabolism | Histocompatibility Antigens Class I - metabolism | Animals | Alleles | Epitopes - chemistry | Mice | Software | Internet | Haplorhini - genetics | Index Medicus
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4. Full Text Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach
by Nielsen, Morten and Lundegaard, Claus and Worning, Peder and Sylvester Hvid, Christina and Lamberth, Kasper and Buus, Søren and Brunak, Søren and Lund, Ole
Bioinformatics (Oxford, England), ISSN 1367-4803, 06/2004, Volume 20, Issue 9, pp. 1388 - 1397
Statistics & Probability | Biochemistry & Molecular Biology | Physical Sciences | Computer Science, Interdisciplinary Applications | Life Sciences & Biomedicine | Technology | Biochemical Research Methods | Computer Science | Mathematics | Biotechnology & Applied Microbiology | Science & Technology | Mathematical & Computational Biology | Fundamental and applied biological sciences. Psychology | Biological and medical sciences | General aspects | Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) | Sequence Analysis, Protein - methods | Reproducibility of Results | Histocompatibility Antigens Class I - immunology | Histocompatibility Antigens Class II - chemistry | Histocompatibility Antigens Class I - chemistry | Epitopes, T-Lymphocyte - chemistry | Protein Interaction Mapping - methods | Sequence Alignment - methods | Algorithms | Histocompatibility Antigens Class II - immunology | Sensitivity and Specificity | Protein Binding | Major Histocompatibility Complex - immunology | Epitopes, T-Lymphocyte - immunology | Binding Sites | Index Medicus
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5. Full Text Improved methods for predicting peptide binding affinity to MHC class II molecules
by Jensen, Kamilla Kjærgaard and Andreatta, Massimo and Marcatili, Paolo and Buus, Søren and Greenbaum, Jason A and Yan, Zhen and Sette, Alessandro and Peters, Bjoern and Nielsen, Morten
Immunology, ISSN 0019-2805, 07/2018, Volume 154, Issue 3, pp. 394 - 406
immunogenic peptides | T‐cell epitope | affinity predictions | peptide–MHC binding | MHC binding specificity | T-cell epitope | Life Sciences & Biomedicine | Immunology | Science & Technology | Amino Acid Sequence | Computational Biology - methods | Reproducibility of Results | Epitopes - metabolism | Humans | Oligopeptides - immunology | Oligopeptides - metabolism | Epitopes - immunology | Epitopes, T-Lymphocyte - chemistry | Histocompatibility Antigens Class II - immunology | Databases, Protein | Protein Binding | Epitope Mapping - methods | Histocompatibility Antigens Class II - metabolism | Epitopes, T-Lymphocyte - immunology | Oligopeptides - chemistry | Histocompatibility antigens | Peptides | Analysis | HLA histocompatibility antigens | T cells | Methods | Antigenic determinants | Binding | Major histocompatibility complex | Immune response | Helper cells | Predictions | Affinity | Lymphocytes T | Histocompatibility antigen HLA | Epitopes | Molecular chains | Index Medicus | Original
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6. Full Text NetMHCIIpan-3.0, a common pan-specific MHC class II prediction method including all three human MHC class II isotypes, HLA-DR, HLA-DP and HLA-DQ
by Karosiene, Edita and Rasmussen, Michael and Blicher, Thomas and Lund, Ole and Buus, Søren and Nielsen, Morten
Immunogenetics (New York), ISSN 0093-7711, 10/2013, Volume 65, Issue 10, pp. 711 - 724
Human Genetics | Gene Function | Allergology | Biomedicine | Immunology | MHC binding specificity | Human leukocyte antigens | Artificial neural networks | T cell epitope | Peptide–MHC binding | MHC class II | Cell Biology | Peptide-MHC binding | Genetics & Heredity | Life Sciences & Biomedicine | Science & Technology | Protein Structure, Tertiary | Amino Acid Sequence | Computational Biology - methods | Reproducibility of Results | Protein Structure, Secondary | Histocompatibility Antigens Class II - classification | Humans | Models, Molecular | Molecular Sequence Data | HLA-DR Antigens - chemistry | HLA-DQ Antigens - immunology | HLA-DR Antigens - genetics | Sequence Homology, Amino Acid | HLA-DP Antigens - chemistry | HLA-DP Antigens - genetics | Histocompatibility Antigens Class II - immunology | HLA-DQ Antigens - genetics | HLA-DQ Antigens - chemistry | HLA-DR Antigens - immunology | Histocompatibility Antigens Class II - genetics | HLA-DP Antigens - immunology | Cluster Analysis | Histocompatibility antigens | Analysis | Methods | HLA histocompatibility antigens | Index Medicus | Amino acid sequence | Tcell epitope
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7. Full Text MHC Class II epitope predictive algorithms
by Nielsen, Morten and Lund, Ole and Buus, Søren and Lundegaard, Claus
Immunology, ISSN 0019-2805, 07/2010, Volume 130, Issue 3, pp. 319 - 328
epitope prediction | human leucocyte antigen | major histocompatibility complex class II | major histocompatibility complex peptide binding | T helper responses | Human leucocyte antigen | Epitope prediction | Major histocompatibility complex class II | Major histocompatibility complex peptide binding | Life Sciences & Biomedicine | Immunology | Science & Technology | Epitopes - immunology | Computational Biology - methods | Animals | Epitopes - metabolism | Histocompatibility Antigens Class II - immunology | Humans | Histocompatibility Antigens Class II - metabolism | Epitopes - chemistry | Histocompatibility Antigens Class II - chemistry | Histocompatibility Antigens Class II - genetics | Epitopes - genetics | Protein Binding - immunology | Algorithms | Universities and colleges | Peptides | Analysis | Antigenic determinants | Methods | Index Medicus | Review
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8. Full Text NetMHCpan, a method for MHC class I binding prediction beyond humans
by Hoof, Ilka and Hoof, Ilka and Peters, Bjoern and Peters, Bjoern and Sidney, John and Sidney, John and Pedersen, Lasse Eggers and Pedersen, Lasse Eggers and Sette, Alessandro and Sette, Alessandro and Lund, Ole and Lund, Ole and Buus, Søren and Buus, Søren and Nielsen, Morten and Nielsen, Morten
Immunogenetics (New York), ISSN 0093-7711, 1/2009, Volume 61, Issue 1, pp. 1 - 13
Allergology | Gene Function | Human Genetics | CTL epitopes | Biomedicine | Immunology | Binding specificity | Artificial neural networks | MHC class I | Non-human primates | Cell Biology | Genetics & Heredity | Life Sciences & Biomedicine | Science & Technology | Neural Networks, Computer | Species Specificity | Humans | Macaca mulatta - immunology | HLA Antigens - genetics | Pan troglodytes - immunology | Histocompatibility Antigens Class I - metabolism | Sus scrofa - genetics | Gorilla gorilla - genetics | Computer Simulation | Protein Interaction Domains and Motifs | Epitopes, T-Lymphocyte - immunology | Gorilla gorilla - immunology | Amino Acid Sequence | Oligopeptides - immunology | Histocompatibility Antigens Class I - immunology | Pan troglodytes - genetics | HLA Antigens - immunology | Oligopeptides - metabolism | HLA Antigens - metabolism | Protein Interaction Mapping | Epitopes, T-Lymphocyte - chemistry | Algorithms | Animals | Models, Biological | Macaca mulatta - genetics | Protein Binding | Genes, MHC Class I | Mice | Immunity, Cellular | Sus scrofa - immunology | Epitopes, T-Lymphocyte - metabolism | Histocompatibility antigens | Peptides | Neural networks | Analysis | HLA histocompatibility antigens | Gorillas | Chemical properties | Universities and colleges | T cells | Methods | Medical research | Immune system | Index Medicus
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9. Full Text NetMHCstab – predicting stability of peptide–MHC‐I complexes; impacts for cytotoxic T lymphocyte epitope discovery
by Jørgensen, Kasper W and Rasmussen, Michael and Buus, Søren and Nielsen, Morten
Immunology, ISSN 0019-2805, 01/2014, Volume 141, Issue 1, pp. 18 - 26
immunoinformatics | MHC–peptide stability | peptide immunogenicity | cytotoxic T lymphocyte epitopes | Cytotoxic T lymphocyte epitopes | MHC-peptide stability | Peptide immunogenicity | Immunoinformatics | Life Sciences & Biomedicine | Immunology | Science & Technology | Models, Immunological | Humans | Peptides - immunology | Histocompatibility Antigens Class I - immunology | Peptides - genetics | Histocompatibility Antigens Class I - genetics | Epitopes, T-Lymphocyte - immunology | Internet | CD8-Positive T-Lymphocytes - immunology | Neural Networks (Computer) | Proteins | Histocompatibility antigens | T cells | Neural networks | HLA histocompatibility antigens | Antigenic determinants | Cytotoxicity | Ligands | Peptides | Index Medicus | Original
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