The NCBI Comparative Genome Viewer (CGV) is an interactive visualization tool for the analysis of whole-genome eukaryotic alignments.

We report a new visualization tool for analysis of whole-genome assembly-assembly alignments, the Comparative Genome Viewer (CGV) (https://ncbi.nlm.nih.

Interactive visualization of whole eukaryote genome alignments using NCBI's Comparative Genome Viewer (CGV).

We report a new visualization tool for analysis of whole genome assembly-assembly alignments, the Comparative Genome Viewer (CGV) (https://ncbi.nlm.nih.

Accessing NCBI data using the NCBI Sequence Viewer and Genome Data Viewer (GDV).

The National Center for Biotechnology Information (NCBI) is an archive providing free access to a wide range and large volume of biological sequence data and literature. Staff scientists at NCBI analyze user-submitted data in the archive, producing gene and SNP annotation and generating sequence alignment tools. NCBI's flagship genome browser, Genome Data Viewer (GDV), displays our in-house RefSeq annotation; is integrated with other NCBI resources such as Gene, dbGaP, and BLAST; and provides a platform for customized analysis and visualization.

Failure dynamics of the global risk network.

Risks threatening modern societies form an intricately interconnected network that often underlies crisis situations. Yet, little is known about how risk materializations in distinct domains influence each other. Here we present an approach in which expert assessments of likelihoods and influence of risks underlie a quantitative model of the global risk network dynamics.

Cascading failures in spatially-embedded random networks.

Cascading failures constitute an important vulnerability of interconnected systems. Here we focus on the study of such failures on networks in which the connectivity of nodes is constrained by geographical distance. Specifically, we use random geometric graphs as representative examples of such spatial networks, and study the properties of cascading failures on them in the presence of distributed flow.

A coarse-grained model for synergistic action of multiple enzymes on cellulose.

Background: Degradation of cellulose to glucose requires the cooperative action of three classes of enzymes, collectively known as cellulases. Endoglucanases randomly bind to cellulose surfaces and generate new chain ends by hydrolyzing β-1,4-D-glycosidic bonds. Exoglucanases bind to free chain ends and hydrolyze glycosidic bonds in a processive manner releasing cellobiose units.

In silico studies of crystalline cellulose and its degradation by enzymes.

In this report, the current state of computational studies on crystalline cellulose is reviewed. The discussion is focused on fully atomistic molecular-dynamics simulations as well as on other computational approaches which are relevant in the context of enzymatic degradation of cellulose. Finally, possible directions and necessary improvements for future computational studies in this challenging research field are summarized.