Cargando…

Hit series selection in noisy HTS data: clustering techniques, statistical tests and data visualisations

Detalles Bibliográficos
Autores principales:	Müller, Christoph, Ormsby, Daniel, Feierberg, Isabella, Engkvist, Ola, Tyrchan, Christian, Hartshorn, Michael J
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2014
Materias:	Poster Presentation
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3980185/ http://dx.doi.org/10.1186/1758-2946-6-S1-P27

Ejemplares similares

HTS explorer
por: Müller, Christoph, et al.
Publicado: (2014)

Clustering noisy data with deterministic annealing
por: Ohlsson, M
Publicado: (1993)

uap: reproducible and robust HTS data analysis
por: Kämpf, Christoph, et al.
Publicado: (2019)

HTS and hit finding in academia – from chemical genomics to drug discovery
por: Frearson, Julie A., et al.
Publicado: (2009)

Changing the HTS Paradigm: AI-Driven Iterative Screening for Hit Finding
por: Dreiman, Gabriel H. S., et al.
Publicado: (2020)

Evaluation of statistical approaches for association testing in noisy drug screening data
por: Smirnov, Petr, et al.
Publicado: (2022)

Identification of Compounds That Interfere with High‐Throughput Screening Assay Technologies
por: David, Laurianne, et al.
Publicado: (2019)

Modeling noisy time-series data of crime with stochastic differential equations
por: Calatayud, Julia, et al.
Publicado: (2022)

Data visualisation approaches for component network meta-analysis: visualising the data structure
por: Freeman, Suzanne C., et al.
Publicado: (2023)

Data visualisation : a handbook for data driven design /
por: Kirk, Andy
Publicado: (2019)

Automated annotation and visualisation of high-resolution spatial proteomic mass spectrometry imaging data using HIT-MAP
por: Guo, G., et al.
Publicado: (2021)

Construction, Visualisation, and Clustering of Transcription Networks from Microarray Expression Data
por: Freeman, Tom C, et al.
Publicado: (2007)

DGW: an exploratory data analysis tool for clustering and visualisation of epigenomic marks
por: Lukauskas, Saulius, et al.
Publicado: (2016)

Visualising disease trajectories from population-wide data
por: Hjaltelin, Jessica Xin, et al.
Publicado: (2023)

Clinical trial data visualisation
por: Gregson, Cassie
Publicado: (2015)

Mental chronometry in big noisy data
por: Wascher, Edmund, et al.
Publicado: (2022)

CD-HIT: accelerated for clustering the next-generation sequencing data
por: Fu, Limin, et al.
Publicado: (2012)

Data visualisation with R: 100 examples
por: Rahlf, Thomas
Publicado: (2017)

Dynamic Phenotypic Clustering in Noisy Ecosystems
por: Ernebjerg, Morten, et al.
Publicado: (2011)

Can Replication Save Noisy Microarray Data?
por: Wernisch, Lorenz
Publicado: (2002)

Calculating the matrix profile from noisy data
por: Hehir, Colin, et al.
Publicado: (2023)

HTS applications
por: Noe, M, et al.
Publicado: (2009)

From Big Data to Artificial Intelligence: chemoinformatics meets new challenges
por: Tetko, Igor V., et al.
Publicado: (2020)

PyNumDiff: A Python package for numerical differentiation of noisy time-series data
por: Van Breugel, Floris, et al.
Publicado: (2022)

Statistical Evaluation of HTS Assays for Enzymatic Hydrolysis of β-Keto Esters
por: Buß, O., et al.
Publicado: (2016)

Transformer-based molecular optimization beyond matched molecular pairs
por: He, Jiazhen, et al.
Publicado: (2022)

RNfuzzyApp: an R shiny RNA-seq data analysis app for visualisation, differential expression analysis, time-series clustering and enrichment analysis
por: Haering, Margaux, et al.
Publicado: (2021)

Plant data visualisation using network graphs
por: Mohamad-Matrol, Afrina Adlyna, et al.
Publicado: (2018)

Innovation in Data Visualisation for Public Policy Making
por: Raineri, Paolo, et al.
Publicado: (2020)

Semantic Data Visualisation for Biomedical Database Catalogues †
por: Pereira, Arnaldo, et al.
Publicado: (2022)

Deep kernel learning of dynamical models from high-dimensional noisy data
por: Botteghi, Nicolò, et al.
Publicado: (2022)

Symbolic Learning and Reasoning With Noisy Data for Probabilistic Anchoring
por: Zuidberg Dos Martires, Pedro, et al.
Publicado: (2020)

Neural ordinary differential equations with irregular and noisy data
por: Goyal, Pawan, et al.
Publicado: (2023)

Visualising statistical models using dynamic nomograms
por: Jalali, Amirhossein, et al.
Publicado: (2019)

Advances in HTS materials
por: Tixador, P
Publicado: (2009)

SMILES-based deep generative scaffold decorator for de-novo drug design
por: Arús-Pous, Josep, et al.
Publicado: (2020)

Molecular optimization by capturing chemist’s intuition using deep neural networks
por: He, Jiazhen, et al.
Publicado: (2021)

ATLAS Open Data: software for visualisation and physics analysis
por: Lo, Ya-Feng
Publicado: (2018)

VeloPix Data Visualisation and Read-out Control
por: Vella, Andrea
Publicado: (2018)

Providing visualisation support for the analysis of anatomy ontology data
por: Dadzie, Aba-Sah, et al.
Publicado: (2005)

Cannot write session to /tmp/vufind_sessions/sess_4qlvquf9plaivnm3nhvne32odj