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Systems Biology: necessary developments and trends
At the end of this definition of Systems Biology through exampling, we discuss ambitions, goals, and challenges relating to this new discipline. We...
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Modular Neural Networks
We describe in this chapter the basic concepts, theory and algorithms of modular and ensemble neural networks. We will also give particular attention...
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Type-1 Fuzzy Logic
This chapter introduces the basic concepts, notation, and basic operations for the type-1 fuzzy sets that will be needed in the following chapters....
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Human Recognition using Face, Fingerprint and Voice
We describe in this chapter a new approach for human recognition using as information the face, fingerprint, and voice of a person. We have described...
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Fingerprint Recognition with Modular Neural Networks and Fuzzy Measures
We describe in this chapter a new approach for fingerprint recognition using modular neural networks with a fuzzy logic method for response...
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Voice Recognition with Neural Networks, Fuzzy Logic and Genetic Algorithms
We describe in this chapter the use of neural networks, fuzzy logic and genetic algorithms for voice recognition. In particular, we consider the case...
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Development of Technetium-99m and Rhenium-188 Radiopharmaceuticals Containing a Terminal Metal–Nitrido Multiple Bond for Diagnosis and Therapy
The chemistry of nitrido complexes of technetium has played an important role in the search of new Tc-99m radiopharmaceuticals and in providing...
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Scientific and technical challenges for systems biology
Systems biology is an emergent discipline, yet can be rooted back almost a century when pioneering thoughts on system-oriented views were discussed....
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Monitoring Multidrug Resistance P-Glycoprotein Drug Transport Activity with Single-Photon Emission Computed Tomography and Positron Emission Tomography Radiopharmaceuticals
Multidrug resistance (MDR) mediated by overexpression of MDR1 P-glycoprotein (Pgp) is one of the best characterized transporter-mediated barriers to...
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From isolation to integration, a systems biology approach for building the Silicon Cell
In the last decade, the field now commonly referred to as systems biology has developed rapidly. With the sequencing of whole genomes and the...
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Systems biology of apoptosis
New approaches are required for the mathematical modelling and system identification of complex signal transduction networks, which are characterized...
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Iterative Single Data Algorithm for Training Kernel Machines from Huge Data Sets: Theory and Performance
The chapter introduces the latest developments and results of Iterative Single Data Algorithm (ISDA) for solving large-scale support vector machines...
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Support Vector Machines – An Introduction
This is a book about learning from empirical data (i.e., examples, samples, measurements, records, patterns or observations) by applying support...
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Cancer Diagnosis and Protein Secondary Structure Prediction Using Support Vector Machines
In this chapter, we use support vector machines (SVMs) to deal with two bioinformatics problems, i.e., cancer diagnosis based on gene expression data...
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Sequential Pattern Mining*
Sequential pattern discovery has emerged as an important research topic in knowledge discovery and data mining with broad applications. Previous...
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Discovering the Factors Affecting the Location Selection of FDI in China*
Since the late 1970s, Foreign Direct Investment (FDI) has played an important role in the economic development of China. However, the growth of FDI...
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Kernel Discriminant Learning with Application to Face Recognition
When applied to high-dimensional pattern classification tasks such as face recognition, traditional kernel discriminant analysis methods often suffer...
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Gas Sensing Using Support Vector Machines
In this chapter we deal with the use of Support Vector Machines in gas sensing. After a brief introduction to the inner workings of multisensor...
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Tachycardia Discrimination in Implantable Cardioverter Defibrillators Using Support Vector Machines and Bootstrap Resampling
Accurate automatic discrimination between supraventricular (SV) and ventricular (V) tachycardia (T) in implantable cardioverter defibrillators (ICD)...
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Improving the Performance of the Support Vector Machine: Two Geometrical Scaling Methods
In this chapter, we discuss two possible ways of improving the performance of the SVM, using geometric methods. The first adapts the kernel by...