2010, World Bank study, ISBN 9780821386224, xiv, 95
The Amazon basin is a key component of the global carbon cycle. Not only is the old-growth rainforests in the basin huge carbon storage with about 120 billion...
Deforestation | Carbon content | Computer simulation | Forest biomass | Climatic factors | Climatic changes | Rain forest plants | Forecasting | Forest microclimatology | Amazon River Region | CLIMATE CHANGE ADAPTATION | CLIMATE SCENARIOS | ATMOSPHERIC RESEARCH | CARBON DIOXIDE LEVELS | EXTREME WEATHER | DRY SEASON | TROPICAL BROADLEAF EVERGREEN | RAINFALL DISTRIBUTIONS | ABOVEGROUND VEGETATION | CLIMATE | METEOROLOGICAL RESEARCH | WIND | CLIMATE CHANGES | GLOBAL SCALE | FOSSIL FUEL EMISSIONS | IMPACT OF CLIMATE | ATMOSPHERE | RAINFALL REDUCTION | PRECIPITATION | CARBON EMISSIONS | URBAN AREAS | TEMPERATURE INCREASE | CARBON CHANGE | CLEAN ENERGY | ENVIRONMENTAL CONDITIONS | LAND USE CHANGE | AMAZON RAINFOREST | CLIMATE CHANGE | ENERGY EFFICIENCY | CLIMATE CHANGE IMPACTS | GLOBAL PRECIPITATION CLIMATOLOGY | SURFACE TEMPERATURES | TROPICAL FORESTS | SURFACE RUNOFF | CONVERGENCE | PLANT GROWTH | TEMPERATURE CHANGES | CARBON STARVATION | CLIMATE RESEARCH | ICE | CLIMATOLOGY | EMISSION SCENARIOS | VEGETATION GROWTH | CLOUDS | FOREST GROWTH | RAINFALL TREND | SCIENTISTS | EMISSIONS | LAND SURFACE | INTERTROPICAL CONVERGENCE ZONE | CLIMATE FORCING | RENEWABLE ENERGY | EVAPOTRANSPIRATION | FOREST TYPES | HYDROLOGY | RAINFALL | ECOSYSTEM STRUCTURE | GLOBAL GREENHOUSE GAS | TROPICAL FOREST BIOMASS | BIOSPHERE | ECOSYSTEM RESILIENCE | CLIMATE SCENARIO | FOREST BIOMASS | TEMPERATURE ANOMALY | FOREST CONSERVATION | ATMOSPHERIC CARBON | ATMOSPHERIC CARBON DIOXIDE | CLIMATE FEEDBACKS | ENDEMIC SPECIES | GLOBAL WARMING | DEFORESTATION SCENARIOS | ITCZ | FERTILIZATION | GREENHOUSE | FOREST BIOMASS ESTIMATE | TROPICS | FOREST COVER | CLIMATE CONDITIONS | CLIMATE IMPACTS | CLIMATE SCIENCE | GLOBAL PRECIPITATION | DRY FORESTS | SEA LEVEL RISE | RESPONSE TO CLIMATE CHANGE | BIOMASS CARBON | CLIMATE SIMULATION | SUSTAINABLE DEVELOPMENT | WATER CYCLE | WEATHER PREDICTION | CLIMATIC RESEARCH | GCM | EVAPORATION | CONVECTIVE PRECIPITATION | TEMPERATURE ANOMALIES | VEGETATION DYNAMICS | GLOBAL AVERAGE SURFACE WARMING | ECOSYSTEM | CLIMATE TRENDS | VEGETATION CHANGE | CLIMATE CHANGE SCENARIOS | FOREST ECOSYSTEMS | WEATHER FORECASTING | FOSSIL FUEL | VEGETATION CARBON | GREENHOUSE GASES | EXTREME WEATHER EVENTS | PHOTOSYNTHESIS | CLIMATIC CHANGES | AIR | CLIMATE IMPACT | FOREST STANDS | SEASONAL RAINFALL | CLIMATE MODELS | EXTREME DRY | GENERAL CIRCULATION MODEL | NITROGEN | EMISSION SCENARIO | CLIMATE-VEGETATION MODEL | GLOBAL VEGETATION | SULPHATE | ATMOSPHERE-OCEAN GENERAL CIRCULATION | CLIMATE SIMULATIONS | CLIMATIC VARIABLE | FOREST DEGRADATION | CLIMATE EXTREMES | TEMPERATURE INDEXES | CENTURY TEMPERATURE | CO2 | GLOBAL EMISSIONS | FOREST CARBON | AMAZONIAN RAINFALL | FOSSIL FUELS | WOODLAND | AEROSOLS | CARBON | WET SEASON | DYNAMIC GLOBAL VEGETATION MODEL | FOREST STRUCTURE | ENVIRONMENTAL ECONOMIST | IMPACTS OF CLIMATE CHANGE | SEASON | ATMOSPHEREOCEAN GENERAL CIRCULATION | AMAZON DEFORESTATION | EMISSIONS SCENARIOS | SURFACE TEMPERATURE | DEFORESTATION | FOREST MICROCLIMATOLOGY | LAND USE | GHG | DROUGHT | EXTREME PRECIPITATION EVENTS | CLIMATE MODEL | CLIMATE PREDICTION | SURFACE MODEL | METHANE | LOSS OF VEGETATION | TREE SPECIES | EXTREME PRECIPITATION | SURFACE PRESSURE | COLORS | CLIMATE EQUILIBRIUM | LIGHTNING | OCEANS | CLIMATE IMPACT RESEARCH | CLIMATIC CONDITIONS | GHGS | INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE | FORESTS | RADIATIVE FORCING | CLIMATE CHANGE PROJECTIONS | RAIN | AMAZON FOREST | EMISSIONS FROM SOILS | CLIMATE RESEARCH UNIT | BIOMASS DENSITY | TEMPERATE FORESTS | EMISSION | CLIMATE POLICIES | EMISSION TRAJECTORIES | TROPICAL FOREST | CRU | CLIMATIC FACTORS | SURFACE TEMPERATURE CHANGE | RAINFALL VARIABILITY | TEMPERATURE CHANGE | HYDROLOGICAL CHANGES | SURFACE TEMPERATURE ANOMALIES | MEAN RAINFALL | AMAZONIAN FOREST | RAINFALL ANOMALIES | CARBON EMISSION | GLOBAL GREENHOUSE GAS EMISSION | IPCC | GLOBAL CARBON CYCLE | FOREST DIEBACK | BIOCLIMATIC LIMITS | CLOUD COVER | ECOSYSTEM RESPONSES | CARBON SINK | FOREST | GLOBAL CLIMATE | GLOBAL EMISSION | FLOODS | LAND USE CHANGES | ANNUAL PRECIPITATION | GLOBAL BIODIVERSITY | INTERNATIONAL CLIMATE POLICY | EXTREME EVENTS | AIR TEMPERATURE | CARBON CONTENT
Deforestation | Carbon content | Computer simulation | Forest biomass | Climatic factors | Climatic changes | Rain forest plants | Forecasting | Forest microclimatology | Amazon River Region | CLIMATE CHANGE ADAPTATION | CLIMATE SCENARIOS | ATMOSPHERIC RESEARCH | CARBON DIOXIDE LEVELS | EXTREME WEATHER | DRY SEASON | TROPICAL BROADLEAF EVERGREEN | RAINFALL DISTRIBUTIONS | ABOVEGROUND VEGETATION | CLIMATE | METEOROLOGICAL RESEARCH | WIND | CLIMATE CHANGES | GLOBAL SCALE | FOSSIL FUEL EMISSIONS | IMPACT OF CLIMATE | ATMOSPHERE | RAINFALL REDUCTION | PRECIPITATION | CARBON EMISSIONS | URBAN AREAS | TEMPERATURE INCREASE | CARBON CHANGE | CLEAN ENERGY | ENVIRONMENTAL CONDITIONS | LAND USE CHANGE | AMAZON RAINFOREST | CLIMATE CHANGE | ENERGY EFFICIENCY | CLIMATE CHANGE IMPACTS | GLOBAL PRECIPITATION CLIMATOLOGY | SURFACE TEMPERATURES | TROPICAL FORESTS | SURFACE RUNOFF | CONVERGENCE | PLANT GROWTH | TEMPERATURE CHANGES | CARBON STARVATION | CLIMATE RESEARCH | ICE | CLIMATOLOGY | EMISSION SCENARIOS | VEGETATION GROWTH | CLOUDS | FOREST GROWTH | RAINFALL TREND | SCIENTISTS | EMISSIONS | LAND SURFACE | INTERTROPICAL CONVERGENCE ZONE | CLIMATE FORCING | RENEWABLE ENERGY | EVAPOTRANSPIRATION | FOREST TYPES | HYDROLOGY | RAINFALL | ECOSYSTEM STRUCTURE | GLOBAL GREENHOUSE GAS | TROPICAL FOREST BIOMASS | BIOSPHERE | ECOSYSTEM RESILIENCE | CLIMATE SCENARIO | FOREST BIOMASS | TEMPERATURE ANOMALY | FOREST CONSERVATION | ATMOSPHERIC CARBON | ATMOSPHERIC CARBON DIOXIDE | CLIMATE FEEDBACKS | ENDEMIC SPECIES | GLOBAL WARMING | DEFORESTATION SCENARIOS | ITCZ | FERTILIZATION | GREENHOUSE | FOREST BIOMASS ESTIMATE | TROPICS | FOREST COVER | CLIMATE CONDITIONS | CLIMATE IMPACTS | CLIMATE SCIENCE | GLOBAL PRECIPITATION | DRY FORESTS | SEA LEVEL RISE | RESPONSE TO CLIMATE CHANGE | BIOMASS CARBON | CLIMATE SIMULATION | SUSTAINABLE DEVELOPMENT | WATER CYCLE | WEATHER PREDICTION | CLIMATIC RESEARCH | GCM | EVAPORATION | CONVECTIVE PRECIPITATION | TEMPERATURE ANOMALIES | VEGETATION DYNAMICS | GLOBAL AVERAGE SURFACE WARMING | ECOSYSTEM | CLIMATE TRENDS | VEGETATION CHANGE | CLIMATE CHANGE SCENARIOS | FOREST ECOSYSTEMS | WEATHER FORECASTING | FOSSIL FUEL | VEGETATION CARBON | GREENHOUSE GASES | EXTREME WEATHER EVENTS | PHOTOSYNTHESIS | CLIMATIC CHANGES | AIR | CLIMATE IMPACT | FOREST STANDS | SEASONAL RAINFALL | CLIMATE MODELS | EXTREME DRY | GENERAL CIRCULATION MODEL | NITROGEN | EMISSION SCENARIO | CLIMATE-VEGETATION MODEL | GLOBAL VEGETATION | SULPHATE | ATMOSPHERE-OCEAN GENERAL CIRCULATION | CLIMATE SIMULATIONS | CLIMATIC VARIABLE | FOREST DEGRADATION | CLIMATE EXTREMES | TEMPERATURE INDEXES | CENTURY TEMPERATURE | CO2 | GLOBAL EMISSIONS | FOREST CARBON | AMAZONIAN RAINFALL | FOSSIL FUELS | WOODLAND | AEROSOLS | CARBON | WET SEASON | DYNAMIC GLOBAL VEGETATION MODEL | FOREST STRUCTURE | ENVIRONMENTAL ECONOMIST | IMPACTS OF CLIMATE CHANGE | SEASON | ATMOSPHEREOCEAN GENERAL CIRCULATION | AMAZON DEFORESTATION | EMISSIONS SCENARIOS | SURFACE TEMPERATURE | DEFORESTATION | FOREST MICROCLIMATOLOGY | LAND USE | GHG | DROUGHT | EXTREME PRECIPITATION EVENTS | CLIMATE MODEL | CLIMATE PREDICTION | SURFACE MODEL | METHANE | LOSS OF VEGETATION | TREE SPECIES | EXTREME PRECIPITATION | SURFACE PRESSURE | COLORS | CLIMATE EQUILIBRIUM | LIGHTNING | OCEANS | CLIMATE IMPACT RESEARCH | CLIMATIC CONDITIONS | GHGS | INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE | FORESTS | RADIATIVE FORCING | CLIMATE CHANGE PROJECTIONS | RAIN | AMAZON FOREST | EMISSIONS FROM SOILS | CLIMATE RESEARCH UNIT | BIOMASS DENSITY | TEMPERATE FORESTS | EMISSION | CLIMATE POLICIES | EMISSION TRAJECTORIES | TROPICAL FOREST | CRU | CLIMATIC FACTORS | SURFACE TEMPERATURE CHANGE | RAINFALL VARIABILITY | TEMPERATURE CHANGE | HYDROLOGICAL CHANGES | SURFACE TEMPERATURE ANOMALIES | MEAN RAINFALL | AMAZONIAN FOREST | RAINFALL ANOMALIES | CARBON EMISSION | GLOBAL GREENHOUSE GAS EMISSION | IPCC | GLOBAL CARBON CYCLE | FOREST DIEBACK | BIOCLIMATIC LIMITS | CLOUD COVER | ECOSYSTEM RESPONSES | CARBON SINK | FOREST | GLOBAL CLIMATE | GLOBAL EMISSION | FLOODS | LAND USE CHANGES | ANNUAL PRECIPITATION | GLOBAL BIODIVERSITY | INTERNATIONAL CLIMATE POLICY | EXTREME EVENTS | AIR TEMPERATURE | CARBON CONTENT
Book
Astronomy and Astrophysics, ISSN 0004-6361, 10/2015, Volume 582, p. A44
A&A 582, A44 (2015) We analyse the main physical parameters and the circumstellar environment of the young Herbig Be star HD 98922. We present AMBER/VLTI high...
stars: formation | stars: pre-main sequence | techniques: high angular resolution | stars: variables: T Tauri, Herbig Ae/Be | circumstellar matter | techniques: interferometric | Physics - Solar and Stellar Astrophysics
stars: formation | stars: pre-main sequence | techniques: high angular resolution | stars: variables: T Tauri, Herbig Ae/Be | circumstellar matter | techniques: interferometric | Physics - Solar and Stellar Astrophysics
Journal Article
IEEE Transactions on Information Theory, ISSN 0018-9448, 11/2016, Volume 62, Issue 11, pp. 6007 - 6018
The entropy region is constructed from vectors of random variables by collecting Shannon entropies of all subvectors. Its shape is studied here by means of...
Ingleton score | Visualization | Shape | non-Shannon inequality | selfadhesivity | Ingleton inequality | Entropy | four-atom conjecture | Channel coding | Entropy region | entropy function | Convolution | information-theoretic inequality | Zhang-Yeung inequality | polymatroid | Network coding | Random variables | matroid | convolution | INFORMATION INEQUALITIES | COMPUTER SCIENCE, INFORMATION SYSTEMS | RANDOM-VARIABLES | ENGINEERING, ELECTRICAL & ELECTRONIC | Error-correcting codes | Matrices | Research | Entropy (Information theory) | Approximation | Entropy (Information) | Decomposition | Closures | Information theory
Ingleton score | Visualization | Shape | non-Shannon inequality | selfadhesivity | Ingleton inequality | Entropy | four-atom conjecture | Channel coding | Entropy region | entropy function | Convolution | information-theoretic inequality | Zhang-Yeung inequality | polymatroid | Network coding | Random variables | matroid | convolution | INFORMATION INEQUALITIES | COMPUTER SCIENCE, INFORMATION SYSTEMS | RANDOM-VARIABLES | ENGINEERING, ELECTRICAL & ELECTRONIC | Error-correcting codes | Matrices | Research | Entropy (Information theory) | Approximation | Entropy (Information) | Decomposition | Closures | Information theory
Journal Article
Frontiers in Microbiology, ISSN 1664-302X, 02/2016, Volume 7
The adaptive humoral immune response is responsible for the generation of antimicrobial proteins known as immunoglobulin molecules or antibodies....
Function | Isotype | Immunoglobulin | Structure | Constant region | Variable region | MOLECULAR CHARACTERIZATION | isotype | constant region | immunoglobulin | PSEUDOMONAS-AERUGINOSA LIPOPOLYSACCHARIDE | MICROBIOLOGY | GROUP-A CARBOHYDRATE | structure | INDUCED CONFORMATIONAL-CHANGES | ANTIGEN-BINDING AFFINITY | 3-DIMENSIONAL STRUCTURE | CRYSTALLOGRAPHIC STRUCTURE | FINE SPECIFICITY | variable region | function | CRYPTOCOCCUS-NEOFORMANS | MONOCLONAL-ANTIBODIES
Function | Isotype | Immunoglobulin | Structure | Constant region | Variable region | MOLECULAR CHARACTERIZATION | isotype | constant region | immunoglobulin | PSEUDOMONAS-AERUGINOSA LIPOPOLYSACCHARIDE | MICROBIOLOGY | GROUP-A CARBOHYDRATE | structure | INDUCED CONFORMATIONAL-CHANGES | ANTIGEN-BINDING AFFINITY | 3-DIMENSIONAL STRUCTURE | CRYSTALLOGRAPHIC STRUCTURE | FINE SPECIFICITY | variable region | function | CRYPTOCOCCUS-NEOFORMANS | MONOCLONAL-ANTIBODIES
Journal Article
Journal of Experimental Medicine, ISSN 0022-1007, 2013, Volume 210, Issue 8, pp. 1501 - 1507
Interactions with cognate antigens recruit activated B cells into germinal centers where they undergo somatic hypermutation (SHM) in V(D)J exons for the...
MEDICINE, RESEARCH & EXPERIMENTAL | ELEMENTS | CLASS SWITCH RECOMBINATION | DNA | TRANSCRIPTION | V(D)J RECOMBINATION | HEAVY-CHAIN LOCUS | VDJ RECOMBINATION | IMMUNOLOGY | INTRONIC ENHANCER | AID | DELETION | Gene Expression | Somatic Hypermutation, Immunoglobulin | VDJ Exons | Cytidine Deaminase - genetics | Germinal Center - immunology | Regulatory Sequences, Nucleic Acid | Gene Expression Regulation | Mice, Knockout | Immunoglobulin kappa-Chains - genetics | Animals | B-Lymphocytes - immunology | Chromatin Immunoprecipitation | Cytidine Deaminase - metabolism | Immunoglobulin Variable Region - genetics | Transcription, Genetic | Mice | 3' Untranslated Regions | Germinal Center - cytology | B-Lymphocytes - metabolism | Immunoglobulin Heavy Chains - genetics | Cytidine Deaminase | Immunoglobulin kappa-Chains | B-Lymphocytes | Life Sciences | Germinal Center | Immunology | Immunoglobulin Heavy Chains | Immunoglobulin Variable Region | Brief Definitive Report
MEDICINE, RESEARCH & EXPERIMENTAL | ELEMENTS | CLASS SWITCH RECOMBINATION | DNA | TRANSCRIPTION | V(D)J RECOMBINATION | HEAVY-CHAIN LOCUS | VDJ RECOMBINATION | IMMUNOLOGY | INTRONIC ENHANCER | AID | DELETION | Gene Expression | Somatic Hypermutation, Immunoglobulin | VDJ Exons | Cytidine Deaminase - genetics | Germinal Center - immunology | Regulatory Sequences, Nucleic Acid | Gene Expression Regulation | Mice, Knockout | Immunoglobulin kappa-Chains - genetics | Animals | B-Lymphocytes - immunology | Chromatin Immunoprecipitation | Cytidine Deaminase - metabolism | Immunoglobulin Variable Region - genetics | Transcription, Genetic | Mice | 3' Untranslated Regions | Germinal Center - cytology | B-Lymphocytes - metabolism | Immunoglobulin Heavy Chains - genetics | Cytidine Deaminase | Immunoglobulin kappa-Chains | B-Lymphocytes | Life Sciences | Germinal Center | Immunology | Immunoglobulin Heavy Chains | Immunoglobulin Variable Region | Brief Definitive Report
Journal Article
Journal of Biological Chemistry, ISSN 0021-9258, 11/2007, Volume 282, Issue 48, pp. 35169 - 35178
B cell-specific expression of immunoglobulin heavy chain (IgH) genes utilizes two cis regulatory regions, the intronic enhancer (E mu), located in the J(H)-C...
B-CELLS | 3' END | VARIANTS | BIOCHEMISTRY & MOLECULAR BIOLOGY | IN-VIVO | TRANSCRIPTION | GENE-EXPRESSION | ENHANCER | DNA REARRANGEMENTS | BETA-GLOBIN LOCUS | IGH LOCUS | Multigene Family | Immunoglobulin Variable Region - chemistry | Gene Expression Regulation | Immunoglobulin Heavy Chains - chemistry | Immunoglobulin Variable Region - metabolism | Molecular Sequence Data | DNA - metabolism | Plasmacytoma - metabolism | DNA - chemistry | Animals | Spleen - metabolism | Models, Biological | Base Sequence | Gene Deletion | Cell Line, Tumor | Immunoglobulin Heavy Chains - metabolism | Mice | Mice, Inbred BALB C | B-Lymphocytes - metabolism
B-CELLS | 3' END | VARIANTS | BIOCHEMISTRY & MOLECULAR BIOLOGY | IN-VIVO | TRANSCRIPTION | GENE-EXPRESSION | ENHANCER | DNA REARRANGEMENTS | BETA-GLOBIN LOCUS | IGH LOCUS | Multigene Family | Immunoglobulin Variable Region - chemistry | Gene Expression Regulation | Immunoglobulin Heavy Chains - chemistry | Immunoglobulin Variable Region - metabolism | Molecular Sequence Data | DNA - metabolism | Plasmacytoma - metabolism | DNA - chemistry | Animals | Spleen - metabolism | Models, Biological | Base Sequence | Gene Deletion | Cell Line, Tumor | Immunoglobulin Heavy Chains - metabolism | Mice | Mice, Inbred BALB C | B-Lymphocytes - metabolism
Journal Article
Virus Genes, ISSN 0920-8569, 2/2018, Volume 54, Issue 1, pp. 111 - 123
The central variable region (CVR) within the B602L gene of the African swine fever virus (ASFV) is highly polymorphic within the 23 ASFV genotypes defined by...
Medical Microbiology | Genotype IX | Thymidine kinase | Biomedicine | African swine fever virus | Plant Sciences | East Africa | CVR | Virology | PIGS | DIAGNOSIS | P72 | REPLICATION | BORDER | VIROLOGY | GENE | GENETICS & HEREDITY | GENOME SEQUENCES | SPREAD | EPIDEMIOLOGY | African Swine Fever Virus - classification | Kenya - epidemiology | African Swine Fever - epidemiology | Uganda - epidemiology | African Swine Fever Virus - genetics | African Swine Fever - virology | Multilocus Sequence Typing | Genetic Variation | Animals | African Swine Fever Virus - isolation & purification | Disease Outbreaks | Swine | Evolution, Molecular | Analysis | Genes | Genetic research | Hog cholera | Livestock | Genetic polymorphisms | African swine fever | Genotyping | Variable region | Outbreaks | Thymidine | Genetic diversity
Medical Microbiology | Genotype IX | Thymidine kinase | Biomedicine | African swine fever virus | Plant Sciences | East Africa | CVR | Virology | PIGS | DIAGNOSIS | P72 | REPLICATION | BORDER | VIROLOGY | GENE | GENETICS & HEREDITY | GENOME SEQUENCES | SPREAD | EPIDEMIOLOGY | African Swine Fever Virus - classification | Kenya - epidemiology | African Swine Fever - epidemiology | Uganda - epidemiology | African Swine Fever Virus - genetics | African Swine Fever - virology | Multilocus Sequence Typing | Genetic Variation | Animals | African Swine Fever Virus - isolation & purification | Disease Outbreaks | Swine | Evolution, Molecular | Analysis | Genes | Genetic research | Hog cholera | Livestock | Genetic polymorphisms | African swine fever | Genotyping | Variable region | Outbreaks | Thymidine | Genetic diversity
Journal Article
IEEE Transactions on Information Theory, ISSN 0018-9448, 11/2016, Volume 62, Issue 11, p. 6007
The entropy region is constructed from vectors of random variables by collecting Shannon entropies of all subvectors. Its shape is studied here by means of...
Approximations | Entropy | Random variables | Experiments | Information theory | Symmetry
Approximations | Entropy | Random variables | Experiments | Information theory | Symmetry
Journal Article
Astronomy and Astrophysics, ISSN 0004-6361, 11/2016, Volume 595
Context. The European Space Agency spacecraft Gaia is expected to observe about 10 000 Galactic Cepheids and over 100 000 Milky Way RR Lyrae stars (a large...
Magellanic Clouds | Methods: data analysis | Stars: variables: RR Lyrae | Stars: general | Stars: variables: Cepheids | Stars: oscillations | CLASSICAL CEPHEIDS | methods: data analysis | stars: general | GRAVITATIONAL LENSING EXPERIMENT | stars: variables: Cepheids | ANOMALOUS CEPHEIDS | SPACED DATA | stars: oscillations | VARIABLE STARS | ASTRONOMY & ASTROPHYSICS | PULSATION MODELS | stars: variables: RR Lyrae | OGLE-III CATALOG | GALACTIC GLOBULAR-CLUSTERS | RADIAL-VELOCITY | LARGE-MAGELLANIC-CLOUD | Magellanic clouds | Pipelines | Stars | Time series | Ecliptic | Cepheid variables | Photometry | Pulsation
Magellanic Clouds | Methods: data analysis | Stars: variables: RR Lyrae | Stars: general | Stars: variables: Cepheids | Stars: oscillations | CLASSICAL CEPHEIDS | methods: data analysis | stars: general | GRAVITATIONAL LENSING EXPERIMENT | stars: variables: Cepheids | ANOMALOUS CEPHEIDS | SPACED DATA | stars: oscillations | VARIABLE STARS | ASTRONOMY & ASTROPHYSICS | PULSATION MODELS | stars: variables: RR Lyrae | OGLE-III CATALOG | GALACTIC GLOBULAR-CLUSTERS | RADIAL-VELOCITY | LARGE-MAGELLANIC-CLOUD | Magellanic clouds | Pipelines | Stars | Time series | Ecliptic | Cepheid variables | Photometry | Pulsation
Journal Article
Journal of Immunological Methods, ISSN 0022-1759, 2008, Volume 338, Issue 1, pp. 67 - 74
Lineage trees describe the microevolution of cells within an organism. They have been useful in the study of B cell affinity maturation, which is based on...
B lymphocyte | Immunoglobulin variable region gene | Lineage tree | Phylogenetic tree | Germinal center | IMMUNE-RESPONSE | phylogenetic tree | SOMATIC HYPERMUTATION | AFFINITY MATURATION | LYMPHOCYTE | lineage tree | ANTIBODY-AFFINITY | BIOCHEMICAL RESEARCH METHODS | germinal center | IMMUNOLOGY | PHYLOGENETIC TREES | LIGHT-CHAIN AMYLOIDOSIS | B-CELL | AUTOIMMUNE-DISEASES | immunoglobulin variable region gene | GERMINAL-CENTERS | Cell Lineage | Immunoglobulin Variable Region - genetics | Algorithms | Phylogeny | Humans | Gene Conversion
B lymphocyte | Immunoglobulin variable region gene | Lineage tree | Phylogenetic tree | Germinal center | IMMUNE-RESPONSE | phylogenetic tree | SOMATIC HYPERMUTATION | AFFINITY MATURATION | LYMPHOCYTE | lineage tree | ANTIBODY-AFFINITY | BIOCHEMICAL RESEARCH METHODS | germinal center | IMMUNOLOGY | PHYLOGENETIC TREES | LIGHT-CHAIN AMYLOIDOSIS | B-CELL | AUTOIMMUNE-DISEASES | immunoglobulin variable region gene | GERMINAL-CENTERS | Cell Lineage | Immunoglobulin Variable Region - genetics | Algorithms | Phylogeny | Humans | Gene Conversion
Journal Article
mAbs, ISSN 1942-0862, 07/2015, Volume 7, Issue 4, pp. 693 - 706
Camelid immunoglobulin variable (IGV) regions were found homologous to their human counterparts; however, the germline V repertoires of camelid heavy and light...
CDR | biologics | human sequence and structural homology | canonical folds | germline variable genes | IgG | antibodies | FR | sequence mining | camelid | Canonical folds | Biologics | Camelid | Antibodies | Human sequence and structural homology | Sequence mining | Germline variable genes | HEAVY-CHAIN ANTIBODIES | STRUCTURAL REPERTOIRE | MEDICINE, RESEARCH & EXPERIMENTAL | WGS | SOMATIC HYPERMUTATION | SEQUENCES | IGLV | MONOCLONAL-ANTIBODY | CANCER | IGHV | PDB | basic local alignment search tools | immunoglobulin heavy chain variable region gene | immunoglobulin light chain kappa variable region gene | REGIONS | immunoglobulin light chain lambda variable region gene | DIVERSITY | BLAST | framework region | Protein Data Bank | LIGHT-CHAINS | variable region family | High-Throughput Genomic database | genes | light chain variable region | IMMUNOGLOBULINS | V family | IGKV | light chain lambda variable region | light chain kappa variable region | Whole Genome Shotgun database | HTG | complementarity-determining region | Protein Structure, Tertiary | Sequence Homology, Amino Acid | Camelids, New World | Animals | Camelus | Humans | Immunoglobulin Variable Region - chemistry | Crystallography, X-Ray | Immunoglobulin Variable Region - genetics | Immunoglobulin Variable Region - immunology | Protein Folding | Life Sciences | Biomolecules | Quantitative Methods | Biochemistry, Molecular Biology
CDR | biologics | human sequence and structural homology | canonical folds | germline variable genes | IgG | antibodies | FR | sequence mining | camelid | Canonical folds | Biologics | Camelid | Antibodies | Human sequence and structural homology | Sequence mining | Germline variable genes | HEAVY-CHAIN ANTIBODIES | STRUCTURAL REPERTOIRE | MEDICINE, RESEARCH & EXPERIMENTAL | WGS | SOMATIC HYPERMUTATION | SEQUENCES | IGLV | MONOCLONAL-ANTIBODY | CANCER | IGHV | PDB | basic local alignment search tools | immunoglobulin heavy chain variable region gene | immunoglobulin light chain kappa variable region gene | REGIONS | immunoglobulin light chain lambda variable region gene | DIVERSITY | BLAST | framework region | Protein Data Bank | LIGHT-CHAINS | variable region family | High-Throughput Genomic database | genes | light chain variable region | IMMUNOGLOBULINS | V family | IGKV | light chain lambda variable region | light chain kappa variable region | Whole Genome Shotgun database | HTG | complementarity-determining region | Protein Structure, Tertiary | Sequence Homology, Amino Acid | Camelids, New World | Animals | Camelus | Humans | Immunoglobulin Variable Region - chemistry | Crystallography, X-Ray | Immunoglobulin Variable Region - genetics | Immunoglobulin Variable Region - immunology | Protein Folding | Life Sciences | Biomolecules | Quantitative Methods | Biochemistry, Molecular Biology
Journal Article
Astronomy and Astrophysics, ISSN 0004-6361, 03/2017, Volume 599, p. A14
Aims. This work analyses the spatial distribution of stars in Taurus with a specific focus on multiple stars and wide pairs in order to derive new constraints...
Stars: variables: T Tauri, Herbig Ae/Be | Stars: statistics | Methods: data analysis | Binaries: visual | Binaries: general | Open clusters and associations: individual: Taurus | BINARY STARS | methods: data analysis | MOLECULAR CLOUDS | HUBBLE-SPACE-TELESCOPE | MAIN-SEQUENCE STARS | binaries: visual | stars: variables: T Tauri, Herbig Ae/Be | GOULD BELT SURVEY | BROWN DWARFS | stars: statistics | ASTRONOMY & ASTROPHYSICS | YOUNG STARS | DENSE CORES | open clusters and associations: individual: Taurus | binaries: general | INITIAL MASS FUNCTION | SOLAR-TYPE STARS | Correlation | Separation | Populations | Star formation | Stars | Cascades | Clustering | Statistics
Stars: variables: T Tauri, Herbig Ae/Be | Stars: statistics | Methods: data analysis | Binaries: visual | Binaries: general | Open clusters and associations: individual: Taurus | BINARY STARS | methods: data analysis | MOLECULAR CLOUDS | HUBBLE-SPACE-TELESCOPE | MAIN-SEQUENCE STARS | binaries: visual | stars: variables: T Tauri, Herbig Ae/Be | GOULD BELT SURVEY | BROWN DWARFS | stars: statistics | ASTRONOMY & ASTROPHYSICS | YOUNG STARS | DENSE CORES | open clusters and associations: individual: Taurus | binaries: general | INITIAL MASS FUNCTION | SOLAR-TYPE STARS | Correlation | Separation | Populations | Star formation | Stars | Cascades | Clustering | Statistics
Journal Article
Astrophysical Journal, ISSN 0004-637X, 06/2015, Volume 806, Issue 1, pp. 79 - 7
delta-sunspots, with highly complex magnetic structures, are very productive in energetic eruptive events, such as X-class flares and homologous eruptions. We...
binaries: eclipsing | stars: oscillations | stars: variables: Cepheids | galaxies: individual (LMC) | RAYLEIGH-TAYLOR INSTABILITY | SPOT FORMATION | FLARES | SUBSURFACE | Sun: photosphere | MAGNETIC-FIELD EVOLUTION | ORIGIN | EMERGING FLUX | ASTRONOMY & ASTROPHYSICS | FILAMENTARY STRUCTURE | sunspots | magnetohydrodynamics (MHD) | CONFIGURATIONS | DYNAMO | Magnetic flux | Computer simulation | Emergence | Inversions | Polarity | Magnetic structure | Formations | Accumulation | Physics - Solar and Stellar Astrophysics | ROTATION | SUNSPOTS | VELOCITY | MAGNETIC FLUX | CONVECTION | SOLAR FLARES | PHOTOSPHERE | MAGNETOHYDRODYNAMICS | POTENTIALS | SUN | COMPUTERIZED SIMULATION | SHEAR | ASTROPHYSICS, COSMOLOGY AND ASTRONOMY | EXPANSION | ZONES | SURFACES
binaries: eclipsing | stars: oscillations | stars: variables: Cepheids | galaxies: individual (LMC) | RAYLEIGH-TAYLOR INSTABILITY | SPOT FORMATION | FLARES | SUBSURFACE | Sun: photosphere | MAGNETIC-FIELD EVOLUTION | ORIGIN | EMERGING FLUX | ASTRONOMY & ASTROPHYSICS | FILAMENTARY STRUCTURE | sunspots | magnetohydrodynamics (MHD) | CONFIGURATIONS | DYNAMO | Magnetic flux | Computer simulation | Emergence | Inversions | Polarity | Magnetic structure | Formations | Accumulation | Physics - Solar and Stellar Astrophysics | ROTATION | SUNSPOTS | VELOCITY | MAGNETIC FLUX | CONVECTION | SOLAR FLARES | PHOTOSPHERE | MAGNETOHYDRODYNAMICS | POTENTIALS | SUN | COMPUTERIZED SIMULATION | SHEAR | ASTROPHYSICS, COSMOLOGY AND ASTRONOMY | EXPANSION | ZONES | SURFACES
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