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Advances in Single Molecule, Real-Time (SMRT) Sequencing
Advances in Single Molecule, Real-Time (SMRT) Sequencing
Autore Ameur Adam
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica 1 electronic resource (128 p.)
Soggetto non controllato Cladobotryum protrusum
allele-specific analysis
low-input DNA
full length RNAseq
de novo genome assembly
de novo assembly
human reference genome
Tricoplusia ni
PacBio single molecule real-time sequencing
secondary metabolite
protein isoforms
bone marrow cell subpopulations
DNA methylation
mycoparasite
human whole-genome sequencing
GRCh38
SMRT sequencing
cytochrome P450 enzyme (CYP)
mRNA isoforms
next generation sequencing
cobweb disease
Swedish population
mosquito
long-read SMRT sequencing
whole genome sequencing
terpenoid
insect genome
optical mapping
Gloeostereum incarnatum
population sequencing
statistical methods
gene expression
single molecule real-time sequencing
PacBio
ISBN 3-03921-701-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Advances in Single Molecule, Real-Time
Record Nr. UNINA-9910367745503321
Ameur Adam  
MDPI - Multidisciplinary Digital Publishing Institute, 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Archaeological Remote Sensing in the 21st Century: (Re)Defining Practice and Theory
Archaeological Remote Sensing in the 21st Century: (Re)Defining Practice and Theory
Autore Verhoeven Geert
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (218 p.)
Soggetto topico Biography & True Stories
Archaeology
Soggetto non controllato relief mapping
visualization
blend modes
digital elevation model
airborne laser scanning
lidar
archaeological prospection
deep learning
citizen science
The Netherlands
archaeology
arid environments
satellite remote sensing
lithological mapping
lithic procurement
chert sourcing
Landsat 8
GIS
ALS
amplitude
radiometric calibration
reflectance
Sicily
transfer learning
historic mining
heritage management
LiDAR
hyperspectral data
submerged areas
cultural heritage monitoring
anomaly detection
MNF
radiative transfer model
Martin Heidegger
technology
mimesis
remote sensing archaeology
cultural context
archaeological remote sensing
satellite mission design
satellite archaeology
archaeological survey
cropmarks
empirical knowledge
alluvial sediments
geomorphological/pedological background
soil spatial infrastructure
statistical methods
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Archaeological Remote Sensing in the 21st Century
Record Nr. UNINA-9910674394303321
Verhoeven Geert  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Cell-Free Nucleic Acids
Cell-Free Nucleic Acids
Autore Nagy Bálint
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica 1 electronic resource (248 p.)
Soggetto non controllato screening
single nucleotide polymorphism
predictive and preventive approach
PTEN
cell-free DNAs
fetal fraction
gestational hypertension
RASSF1
CDH1
RT-PCR
cfDNA
statistical models
hematopoietic stem cell transplantation
NanoString
solid organ transplantation
copy number variants
sarcomas
liquid biopsy
obesity
fetal DNA
neutrophil extracellular traps
mammography
non-invasive prenatal testing
ovarian cancer
circulating miRNA
pyrosequencing
growth retardation
preeclampsia
gestational diabetes mellitus
biomarker
inflammatory bowel disease
multi-level diagnostics
PAX1
population study
nuclease activity
NETosis
omics
piRNA
cell-free DNA
prediction
leiomyosarcomas
network analysis
NGS
statistical methods
circulating nucleic acids
deletion/insertion polymorphism
gender differences
leiomyomas
fetal growth restriction
blood plasma
exosomes
miRNA
pregnancy-related complications
NIPT
genetic marker
cell-free nucleic acids
extracellular vesicles
expression
next generation sequencing
breast cancer
individualized patient profile
circulating tumor cells
maternal serum screening
personalized medicine
embryo culture medium
C19MC microRNA
DNA
cell-free RNAs
z-score
fetal cells
microchimerism
aging
plasma
ISBN 3-03928-075-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910372783603321
Nagy Bálint  
MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Data mining for the social sciences : an introduction / / Paul Attewell and David B. Monaghan
Data mining for the social sciences : an introduction / / Paul Attewell and David B. Monaghan
Autore Attewell Paul A. <1949->
Pubbl/distr/stampa Oakland, California : , : University of California Press, , 2015
Descrizione fisica 1 online resource (265 p.)
Disciplina 006.3/12
Soggetto topico Social sciences - Data processing
Social sciences - Statistical methods
Data mining
Soggetto non controllato analyzing data
bayesian networks
big data
bootstrapping
business analytics
chaid
classification and regression trees
classification trees
confusion matrix
data analysis
data mining
data processing
data scholarship
data science
hardware for data mining
heteroscedasticity
naive bayes
partition trees
permutation tests
scholarly data
social science
social scientists
software for data mining
statistical methods
statistical modeling
studying data
text mining
vif regression
weka
ISBN 0-520-28098-9
0-520-96059-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Front matter -- CONTENTS -- ACKNOWLEDGMENTS -- 1. WHAT IS DATA MINING? -- 2. CONTRASTS WITH THE CONVENTIONAL STATISTICAL APPROACH -- 3. SOME GENERAL STRATEGIES USED IN DATA MINING -- 4. IMPORTANT STAGES IN A DATA MINING PROJECT -- 5. PREPARING TRAINING AND TEST DATASETS -- 6. VARIABLE SELECTION TOOLS -- 7. CREATING NEW VARIABLES -- 8. EXTRACTING VARIABLES -- 9. CLASSIFIERS -- 10. CLASSIFICATION TREES -- 11. NEURAL NETWORKS -- 12. CLUSTERING -- 13. LATENT CLASS ANALYSIS AND MIXTURE MODELS -- 14. ASSOCIATION RULES -- CONCLUSION. Where Next? -- BIBLIOGRAPHY -- NOTES -- INDEX
Record Nr. UNINA-9910788152303321
Attewell Paul A. <1949->  
Oakland, California : , : University of California Press, , 2015
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Data mining for the social sciences : an introduction / / Paul Attewell and David B. Monaghan
Data mining for the social sciences : an introduction / / Paul Attewell and David B. Monaghan
Autore Attewell Paul A. <1949->
Pubbl/distr/stampa Oakland, California : , : University of California Press, , 2015
Descrizione fisica 1 online resource (265 p.)
Disciplina 006.3/12
Soggetto topico Social sciences - Data processing
Social sciences - Statistical methods
Data mining
Soggetto non controllato analyzing data
bayesian networks
big data
bootstrapping
business analytics
chaid
classification and regression trees
classification trees
confusion matrix
data analysis
data mining
data processing
data scholarship
data science
hardware for data mining
heteroscedasticity
naive bayes
partition trees
permutation tests
scholarly data
social science
social scientists
software for data mining
statistical methods
statistical modeling
studying data
text mining
vif regression
weka
ISBN 0-520-28098-9
0-520-96059-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Front matter -- CONTENTS -- ACKNOWLEDGMENTS -- 1. WHAT IS DATA MINING? -- 2. CONTRASTS WITH THE CONVENTIONAL STATISTICAL APPROACH -- 3. SOME GENERAL STRATEGIES USED IN DATA MINING -- 4. IMPORTANT STAGES IN A DATA MINING PROJECT -- 5. PREPARING TRAINING AND TEST DATASETS -- 6. VARIABLE SELECTION TOOLS -- 7. CREATING NEW VARIABLES -- 8. EXTRACTING VARIABLES -- 9. CLASSIFIERS -- 10. CLASSIFICATION TREES -- 11. NEURAL NETWORKS -- 12. CLUSTERING -- 13. LATENT CLASS ANALYSIS AND MIXTURE MODELS -- 14. ASSOCIATION RULES -- CONCLUSION. Where Next? -- BIBLIOGRAPHY -- NOTES -- INDEX
Record Nr. UNINA-9910814373503321
Attewell Paul A. <1949->  
Oakland, California : , : University of California Press, , 2015
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Natural Background Levels in Groundwater
Natural Background Levels in Groundwater
Autore Preziosi Elisabetta
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 electronic resource (202 p.)
Soggetto topico Research & information: general
Environmental economics
Pollution control
Soggetto non controllato ambient background values
probability plot
modified Lepeltier method
pre-selection method
LOQ
groundwater body
Croatia
natural background levels
software implementation
parameters estimation
statistical methods
component separation method
groundwater quality
groundwater level
geostatistics
t-test
spatial distribution modeling
natural background
conceptual model
preselection
nitrates
confidence level
arsenic
sites under remediation
site-specific data
Ferrara
trace metals
Lanzo Massif
ultramafic rocks
ophiolites
chromium
hexavalent chromium
nickel
neutral mine drainage
groundwater
Italian guidelines
cadmium
copper
zinc
Denmark
natural background level
water quality
anthropogenic pressure
trace element
groundwater monitoring
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910566465203321
Preziosi Elisabetta  
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Overcoming Data Scarcity in Earth Science
Overcoming Data Scarcity in Earth Science
Autore Etcheverry Venturini Lorena
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica 1 electronic resource (94 p.)
Soggetto non controllato geophysical monitoring
data scarcity
missing data
climate extreme indices (CEIs)
rule extraction
Dataset Licensedatabase
data assimilation
data imputation
support vector machines
environmental observations
multi-class classification
earth-science data
remote sensing
magnetotelluric monitoring
soil texture calculator
machine learning
ClimPACT
invasive species
species distribution modeling
3D-Var
ensemble learning
data quality
water quality
microhabitat
k-Nearest Neighbors
Expert Team on Climate Change Detection and Indices (ETCCDI)
decision trees
processing
attribute reduction
Expert Team on Sector-specific Climate Indices (ET-SCI)
core attribute
rough set theory
GLDAS
arthropod vector
environmental modeling
statistical methods
ISBN 3-03928-211-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910404080803321
Etcheverry Venturini Lorena  
MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Small sample size solutions : a guide for applied researchers and practitioners / / edited by Rens van de Schoot and Milica Miočević
Small sample size solutions : a guide for applied researchers and practitioners / / edited by Rens van de Schoot and Milica Miočević
Autore van de Schoot Rens
Pubbl/distr/stampa Taylor & Francis, 2020
Descrizione fisica 1 online resource (xiv, 269 pages) : digital, PDF file(s)
Disciplina 001.42
Collana European Association of Methodology series
Soggetto topico Research - Methodology
Data sets
Soggetto non controllato statistical methods
researchers
statistical model
research
small sample
estimation
population
variables
observations
social sciences
behavioral sciences
medical sciences
epidemiology
psychology
marketing
economics
analysis
ISBN 1-000-76101-0
1-000-76108-8
0-367-22222-1
0-429-27387-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction (Van de Schootand Miočević) List of Symbols Part I: Bayesian solutions 1. Introduction to Bayesian statistics(Miočević, Levy,and van de Schoot) 2.The role of exchangeability in sequential updating of findings from small studies and the challenges of identifying exchangeable data sets (Miočević, Levy,and Savord) 3. A tutorial on using the WAMBS checklist to avoid the misuse of Bayesian statistics(van de Schoot, Veen, Smeets, Winter,and Depaoli) 4. The importance of collaboration in Bayesian analyses with small samples (Veenand Egberts) 5. A tutorial on Bayesian penalized regression with shrinkage priors for small sample sizes (van Erp) PartII: n=1 6. One by one: the designand analysis of replicated randomized single-case experiments(Onghena) 7. Single-case experimental designs in clinical intervention research (Maricand van der Werff) 8. How to improve the estimation of a specific examinee's (n=1)math ability when test data are limited(Lekand Arts) 9. Combining evidence over multiple individual analyses(Klaassen) 10. Going multivariate in clinical trial studies: a Bayesian framework for multiple binary outcomes(Kavelaars) PartIII: Complex hypotheses and models 11. An introduction to restriktor: evaluating informative hypotheses for linear models (VanbrabantandRosseel) 12. Testing replication with small samples: applications to ANOVA(Zondervan-Zwijnenburgand Rijshouwer) 13. Small sample meta-analyses: exploring heterogeneity using MetaForest (van Lissa) 14. Item parcels as indicators: why, when, and how to use them in small sample research(Rioux, Stickley, Odejimi,and Little) 15. Small samples in multilevel modeling(Hoxand McNeish) 16. Small sample solutions for structural equation modeling(Rosseel) 17. SEM with small samples: two-step modeling and factor score regression versus Bayesian estimation with informative priors (Smidand Rosseel) 18. Important yet unheeded: some small sample issues that are often overlooked(Hox) Index
Record Nr. UNINA-9910377813603321
van de Schoot Rens  
Taylor & Francis, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Social learning [[electronic resource] ] : an introduction to mechanisms, methods, and models / / William Hoppitt and Kevin N. Laland
Social learning [[electronic resource] ] : an introduction to mechanisms, methods, and models / / William Hoppitt and Kevin N. Laland
Autore Hoppitt William
Edizione [Course Book]
Pubbl/distr/stampa Princeton, : Princeton University Press, 2013
Descrizione fisica 1 online resource (320 p.)
Disciplina 591.5/14
Altri autori (Persone) LalandKevin N
Soggetto topico Learning in animals - Research - Methodology
Social learning - Research - Methodology
Psychology, Comparative - Research - Methodology
Soggetto non controllato Aristotle
acquisition
animal culture
animals
asocial learning
behavior
behavioral repertoires
behavioral research
behavioral trait
biological evolution
causal modeling
child development
children
controlled diffusion
cultural evolution
cultural transmission
decision making
developmental methods
diffusion curve analysis
diffusion data
diffusion experiments
diffusion of innovation
diffusion
ecological hypothesis
experimental manipulations
fear
frequency-dependent biases
gene-culture coevolution
genetic hypothesis
group contrasts approach
hierarchical control
imitation
inadvertent coaching
innovation
laboratory experiments
learning heuristics
mathematical methods
meta-strategies
model-fitting approach
modeling
network-based diffusion analysis
neural circuitry
neuroendocrinological studies
neutral models
observational conditioning
observational data
observational learning
opportunity providing
option choice
random copying
reaction-diffusion models
research methods
response facilitation
social experience
social facilitation
social foraging theory
social learning mechanisms
social learning research
social learning strategies
social learning
social network
social transmission
statistical methods
statistical modeling
stimulus enhancement
success biases
translocation experiments
transmission chains
ISBN 9780691150710
1400846501
1299652131
Classificazione CZ 8000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Contents -- Acknowledgments -- Social Learning -- Chapter 1. Introduction -- Chapter 2. A Brief History of Social Learning Research -- Chapter 3. Methods for Studying Social Learning in the Laboratory -- Chapter 4. Social Learning Mechanisms -- Chapter 5. Statistical Methods for Diffusion Data -- Chapter 6. Repertoire- Based Methods for Detecting and Quantifying Social Transmission -- Chapter 7. Developmental Methods for Studying Social Learning -- Chapter 8. Social Learning Strategies -- Chapter 9. Modeling Social Learning and Culture -- Chapter 10. Conclusions -- References -- Index
Record Nr. UNINA-9910790946703321
Hoppitt William  
Princeton, : Princeton University Press, 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Social learning [[electronic resource] ] : an introduction to mechanisms, methods, and models / / William Hoppitt and Kevin N. Laland
Social learning [[electronic resource] ] : an introduction to mechanisms, methods, and models / / William Hoppitt and Kevin N. Laland
Autore Hoppitt William
Edizione [Course Book]
Pubbl/distr/stampa Princeton, : Princeton University Press, 2013
Descrizione fisica 1 online resource (320 p.)
Disciplina 591.5/14
Altri autori (Persone) LalandKevin N
Soggetto topico Learning in animals - Research - Methodology
Social learning - Research - Methodology
Psychology, Comparative - Research - Methodology
Soggetto non controllato Aristotle
acquisition
animal culture
animals
asocial learning
behavior
behavioral repertoires
behavioral research
behavioral trait
biological evolution
causal modeling
child development
children
controlled diffusion
cultural evolution
cultural transmission
decision making
developmental methods
diffusion curve analysis
diffusion data
diffusion experiments
diffusion of innovation
diffusion
ecological hypothesis
experimental manipulations
fear
frequency-dependent biases
gene-culture coevolution
genetic hypothesis
group contrasts approach
hierarchical control
imitation
inadvertent coaching
innovation
laboratory experiments
learning heuristics
mathematical methods
meta-strategies
model-fitting approach
modeling
network-based diffusion analysis
neural circuitry
neuroendocrinological studies
neutral models
observational conditioning
observational data
observational learning
opportunity providing
option choice
random copying
reaction-diffusion models
research methods
response facilitation
social experience
social facilitation
social foraging theory
social learning mechanisms
social learning research
social learning strategies
social learning
social network
social transmission
statistical methods
statistical modeling
stimulus enhancement
success biases
translocation experiments
transmission chains
ISBN 9780691150710
1400846501
1299652131
Classificazione CZ 8000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Contents -- Acknowledgments -- Social Learning -- Chapter 1. Introduction -- Chapter 2. A Brief History of Social Learning Research -- Chapter 3. Methods for Studying Social Learning in the Laboratory -- Chapter 4. Social Learning Mechanisms -- Chapter 5. Statistical Methods for Diffusion Data -- Chapter 6. Repertoire- Based Methods for Detecting and Quantifying Social Transmission -- Chapter 7. Developmental Methods for Studying Social Learning -- Chapter 8. Social Learning Strategies -- Chapter 9. Modeling Social Learning and Culture -- Chapter 10. Conclusions -- References -- Index
Record Nr. UNINA-9910809665503321
Hoppitt William  
Princeton, : Princeton University Press, 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui