Search Results - subject:"Preprocessing"

Efficient preprocessing for VLSI optimization problems

Hare, W.; Liu, M.; Terlaky, T. - In: Computational Optimization and Applications 45 (2010) 3, pp. 475-493

Persistent link: https://www.econbiz.de/10008552380

An integrated fuzzy regression algorithm for energy consumption estimation with non-stationary data: A case study of Iran

Azadeh, A.; Saberi, M.; Seraj, O. - In: Energy 35 (2010) 6, pp. 2351-2366

from fuzzy regression and time series model is selected by the Granger-Newbold. Also, the impact of data preprocessing on …

Persistent link: https://www.econbiz.de/10010809152

An implementation of a statistical language based on JAVA

Fujiwara, Takeshi; Nakano, Junji; Yamamoto, Yoshikazu; … - 2001

preprocessing approach. This implementation brings several advantages such as reduction of development costs, effective uses of …

Persistent link: https://www.econbiz.de/10010310344

An implementation of a statistical language based on JAVA

Fujiwara, Takeshi; Nakano, Junji; Yamamoto, Yoshikazu; … - Sonderforschungsbereich 373, Quantifikation und … - 2001

preprocessing approach. This implementation brings several advantages such as reduction of development costs, effective uses of …

Persistent link: https://www.econbiz.de/10010956465

Issues of Processing and Multiple Testing of SELDI-TOF MS Proteomic Data

Birkner, Merrill; Hubbard, Alan; Laan, Mark van der; … - In: Statistical Applications in Genetics and Molecular Biology 5 (2009) 1, pp. 11-11

A new data filtering method for SELDI-TOF MS proteomic spectra data is described. We examined technical repeats (2 per subject) of intensity versus m/z (mass/charge) of bone marrow cell lysate for two groups of childhood leukemia patients: acute myeloid leukemia (AML) and acute lymphoblastic...

Persistent link: https://www.econbiz.de/10005046607

Organizing a Competition on Clinical Mass Spectrometry Based Proteomic Diagnosis

Mertens, Bart - In: Statistical Applications in Genetics and Molecular Biology 7 (2008) 2, pp. 3-3

preprocessing steps carried out, with references to appropriate sources describing algorithms used, dimensionalities, definition of …

Persistent link: https://www.econbiz.de/10005585067

A Cross-Validation Study to Select a Classification Procedure for Clinical Diagnosis Based on Proteomic Mass Spectrometry

Valkenborg, Dirk; Sanden, Suzy Van; Lin, Dan; Kasim, Adetayo - In: Statistical Applications in Genetics and Molecular Biology 7 (2008) 2, pp. 12-12

We present an approach to construct a classification rule based on the mass spectrometry data provided by the organizers of the "Classification Competition on Clinical Mass Spectrometry Proteomic Diagnosis Data." Before constructing a classification rule, we attempted to pre-process the data and...

Persistent link: https://www.econbiz.de/10005752552

Saturation and Quantization Reduction in Microarray Experiments using Two Scans at Different Sensitivities

Jorge GarcÃÂa de la Nava; Hijum, Sacha van; … - In: Statistical Applications in Genetics and Molecular Biology 3 (2007) 1, pp. 11-11

We present a mathematical model to extend the dynamic range of gene expression data measured by laser scanners. The strategy is based on the rather simple but novel idea of producing two images with different scanner sensitivities, obtaining two different sets of expression values: the first is...

Persistent link: https://www.econbiz.de/10005585060

Technical and Financial Feasibility Analysis of Distributed Bioprocessing Using Regional Biomass Pre-Processing Centers

Carolan, Joseph; Joshi, Satish; Dale, Bruce - In: Journal of Agricultural & Food Industrial Organization 5 (2007) 2, pp. 1203-1203

local environmental impacts. We propose a network of regional biomass preprocessing centers (RBPC) that form an extended …

Persistent link: https://www.econbiz.de/10005751132

Issues of Processing and Multiple Testing of SELDI-TOF MS Proteomic Data

Birkner, Merrill; Hubbard, Alan; Laan, Mark van der; … - In: Statistical Applications in Genetics and Molecular Biology 5 (2007) 1, pp. 11-11

Persistent link: https://www.econbiz.de/10005246517