Here's a comprehensive reference covering the computational frameworks and techniques needed to help research scientists and professionals in computer science, biology, chemistry, pharmaceutical science, and physics solve complex biological problems. Written by leading experts in the field, this practical resource gives detailed descriptions of core subjects, including biological network modeli...

It is quite ironic that the uncertainty about the number of human genes (28,000–120,000) (Ewing and Green 2000; Liang et al. 2000; Roest Crollius et al. 2000) appears to increase as the determination of the human genome sequence is nearing completion. I shall contend here that this paradox reveals deep epistemological problems, and that “bioinformatics”—a term coined in 1990 to define the use o...

Microscopy of cells has changed dramatically since its early days in the mid-seventeenth century. Image analysis has concurrently evolved from measurements of hand drawings and still photographs to computational methods that (semi-) automatically quantify objects, distances, concentrations, and velocities of cells and subcellular structures. Today's imaging technologies generate a wealth of dat...

Rule-based formalisms for modelling biochemical pathways such as Kappa, BioNetGen and PySB have emerged as powerful tools for the analysis of biochemical pathways. They allow concise, intuitive models to be developed, and by avoiding through the use of rules the combinatorial explosion in the number of biochemical species that befalls traditional techniques, they make in-silico experimentation ...

Systems biology is a broad field that incorporates both computational and experimental approaches to provide a system level understanding of biological function. Initial forays into computational systems biology have focused on a variety of biological networks such as protein-protein interaction, signaling, transcription and metabolic networks. In this review we will provide an overview of avai...

Algebraic combinatorics for computational biology by Nicholas Karl Eriksson Doctor of Philosophy in Mathematics University of California, Berkeley Professor Bernd Sturmfels, Chair Algebraic statistics is the study of the algebraic varieties that correspond to discrete statistical models. Such statistical models are used throughout computational biology, for example to describe the evolution of ...

Olfactory receptors, in addition to being involved in first step of the physiological processes that leads to olfaction, occupy an important place in mammalian genomes. ORs constitute super families in these genomes. Elucidating ol-factory receptor function at a molecular level can be aided by a computationally derived structure and an understanding of its interactions with odor molecules. Expe...

Technological advances in genomics and imaging have led to an explosion of molecular and cellular profiling data from large numbers of samples. This rapid increase in biological data dimension and acquisition rate is challenging conventional analysis strategies. Modern machine learning methods, such as deep learning, promise to leverage very large data sets for finding hidden structure within t...