数据库

Mathematical and computational models have become indispensable tools for integrating and interpreting heterogeneous biological data, understanding fundamental principles of biological system functions, genera�ting reliable testable hypotheses, and identif ...

A large number of genome-scale networks, including protein–protein and genetic interaction networks, are now available for several organisms. In parallel, many studies have focused on analyzing, characterizing, and modeling these networks. Beyond investigating the topolog ...

The yeast two-hybrid (Y2H) system is a powerful tool to identify binary protein–protein interactions. Here, we describe array-based two-hybrid methods that use defined libraries of open reading frames (ORFs) and pooled prey library screenings that use random genomic or cDNA libraries. ...

To understand the workings of the living cell, we need to characterize protein assemblies that constitute the cell (for example, the ribosome, 26S proteasome, and the nuclear pore complex). A reliable high-resolution structural characterization of these assemblies is frequently be ...

Cytoscape is an open-source software package that is widely used to integrate and visualize diverse data sets in biology. This chapter explains how to use Cytoscape to integrate open-source chemical information with a biological network. By visualizing information about known compo ...

Mapping epistatic (or genetic) interactions has emerged as an important network biology approach for establishing functional relationships among genes and proteins. Epistasis networks are complementary to physical protein interaction networks, providing valuable in ...

Here, we present a detailed method for generating a dynamic transcriptional regulatory network from large-scale chromatin immunoprecipitation data, and functional analysis of participating factors through the identification and characterization of significantly o ...

Molecular expression patterns have often been used for patient classification in oncology in an effort to improve prognostic prediction and treatment compatibility. This effort is, however, hampered by the highly heterogeneous data often seen in the molecular analysis of cancer. The ...

Rarely acting in isolation, it is invariably the physical associations among proteins that define their biological activity, necessitating the study of the cellular meshwork of protein–protein interactions (PPI) before a full appreciation of gene function can be achieved. The past ...

Protein–protein interactions are key to many aspects of the cell, including its cytoskeletal structure, the signaling processes in which it is involved, or its metabolism. Failure to form protein complexes or signaling cascades may sometimes translate into pathologic conditions s ...

Gene-set enrichment analysis finds functionally coherent gene-sets, such as pathways, that are statistically overrepresented in a given gene list. Ideally, the number of resulting sets is smaller than the number of genes in the list, thus simplifying interpretation. However, the incr ...

Bioinformatic methods to predict protein–protein interactions (PPI) via coevolutionary analysis have �positioned themselves to compete alongside established in vitro methods, despite a lack of understanding for the underlying molecular mechanisms of the coevolution ...

DNA sequences are important sources of data for phylogenetic analysis. Nowadays, DNA sequencing is a routine technique in molecular biology laboratories. However, there are specific questions associated with project design and sequencing of plant samples for phylogenetic anal ...

Microbes exist naturally in a wide range of environments in communities where their interactions are significant, spanning the extremes of high acidity and high temperature environments to soil and the ocean. We present a practical discussion of three different approaches for modeli ...

The sheer volume of biomedical research threatens to overwhelm the capacity of individuals to effectively process this information. Adding to this challenge is the multiscale nature of both biological systems and the research community as a whole. Given this volume and rate of generation ...

The immune response to pathogens is a result of complex interactions among many cell types and a large number of molecular processes. As such it poses numerous challenges for modeling, simulation, and analysis. In this work we aim at addressing major issues regarding modeling of large biologic ...

Mathematical modeling and computer simulation have become crucial to biological fields from genomics to ecology. However, multicell, tissue-level simulations of development and disease have lagged behind other areas because they are mathematically more complex and lack easy ...

Regression analysis is indispensible for quantitative understanding of biological systems and for developing accurate computational models. By applying regression analysis, one can validate models and quantify components of the system, including ones that cannot be obser ...

Spatially realistic diffusion-reaction simulations supplement traditional experiments and provide testable hypotheses for complex physiological systems. To date, however, the creation of realistic 3D cell models has been difficult and time-consuming, typically invo ...

A general methodology is described for improving the therapeutic properties of protein drugs by engineering novel intracellular trafficking pathways. Procedures for cellular trafficking experiments and mathematical modeling of trafficking pathways are presented. Pr ...