Knowledge-guided analysis of "omics" data using the KnowEnG cloud platform.

We present Knowledge Engine for Genomics (KnowEnG), a free-to-use computational system for analysis of genomics data sets, designed to accelerate biomedical discovery. It includes tools for popular bioinformatics tasks such as gene prioritization, sample clustering, gene set analysis, and expression signature analysis. The system specializes in "knowledge-guided" data mining and machine learning algorithms, in which user-provided data are analyzed in light of prior information about genes, aggregated from numerous knowledge bases and encoded in a massive "Knowledge Network." KnowEnG adheres to "FAIR" principles (findable, accessible, interoperable, and reuseable): its tools are easily portable to diverse computing environments, run on the cloud for scalable and cost-effective execution, and are interoperable with other computing platforms. The analysis tools are made available through multiple access modes, including a web portal with specialized visualization modules. We demonstrate the KnowEnG system's potential value in democratization of advanced tools for the modern genomics era through several case studies that use its tools to recreate and expand upon the published analysis of cancer data sets.

ClusterEnG: an interactive educational web resource for clustering and visualizing high-dimensional data.

SUMMARY: Clustering is one of the most common techniques used in data analysis to discover hidden structures by grouping together data points that are similar in some measure into clusters. Although there are many programs available for performing clustering, a single web resource that provides both state-of-the-art clustering methods and interactive visualizations is lacking. ClusterEnG (acronym for Clustering Engine for Genomics) provides an interface for clustering big data and interactive visualizations including 3D views, cluster selection and zoom features. ClusterEnG also aims at educating the user about the similarities and differences between various clustering algorithms and provides clustering tutorials that demonstrate potential pitfalls of each algorithm. The web resource will be particularly useful to scientists who are not conversant with computing but want to understand the structure of their data in an intuitive manner. AVAILABILITY: ClusterEnG is part of a bigger project called KnowEnG (Knowledge Engine for Genomics) and is available at http://education.knoweng.org/clustereng. CONTACT: songi@illinois.edu.

Residue Specific and Chirality Dependent Interactions between Carbon Nanotubes and Flagellin.

Flagellum is a lash-like cellular appendage found in many single-celled living organisms. The flagellin protofilaments contain 11-helix dual turn structure in a single flagellum. Each flagellin consists of four sub-domains - two inner domains (D0, D1) and two outer domains (D2, D3). While inner domains predominantly consist of α-helices, the outer domains are primarily beta sheets with D3. In flagellum, the outermost sub-domain is the only one that is exposed to the native environment. This study focuses on the interactions of the residues of D3 of an R-type flagellin with 5nm long chiral (5,15) and arm-chair (12,12) single-walled carbon nanotubes (SWNT) using molecular dynamics simulation. It presents the interactive forces between the SWNT and the residues of D3 from the perspectives of size and chirality of the SWNT. It is found that the metallic (arm-chair) SWNT interacts the most with glycine and threonine residues through van der Waals and hydrophobic interactions, whereas the semiconducting (chiral) SWNT interacts largely with the area of protein devoid of glycine by van der Waals, hydrophobic interactions, and hydrogen bonding. This indicates a crucial role that glycine plays in distinguishing metallic from semiconducting SWNTs.

A flagellum based study of semiconductor nanofabrication through magnetotaxis.

Magnetospirillum magneticum (AMB-1), which belong to alpha-protobacterium are gram-negative, single-celled prokaryotic organisms consisting of a lash-like cellular appendage called flagella. These filamentous structures are made up of a protein called flagellin that in turn consist of four sub-domains, two inner domains (D0, D1) made up of alpha-helices and two outer domains (D2, D3) made up of beta sheets. It is wrapped in a helical fashion around the longitudinal filament with the outermost sub-domain (D3) exposed to the surrounding environment. This study focuses on the interaction of the D3 with semiconducting as well as metallic single-walled carbon nanotubes (m-SWNT) and in turn presents the interactive forces between the SWNT and D3 from the perspective of size and type of SWNT. It is found that the SWNT interacts the most with glycine and threonine residues of flagellin both electrostatically as well as through van der waals. Further, the viability of magnetotactic bacteria Magnetospirillum magneticum (AMB-1) in the presence of SWNT is experimentally investigated and it is found that magnetotaxis in AMB-1 is preserved without any toxic effects due to SWNT. It is proposed that AMB-1 can be used as an efficient carrier of carbon nanotubes through its flagellum for semiconductor nanofabrication tasks.

InvertNet: a new paradigm for digital access to invertebrate collections.

InvertNet, one of the three Thematic Collection Networks (TCNs) funded in the first round of the U.S. National Science Foundation's Advancing Digitization of Biological Collections (ADBC) program, is tasked with providing digital access to ~60 million specimens housed in 22 arthropod (primarily insect) collections at institutions distributed throughout the upper midwestern USA. The traditional workflow for insect collection digitization involves manually keying information from specimen labels into a database and attaching a unique identifier label to each specimen. This remains the dominant paradigm, despite some recent attempts to automate various steps in the process using more advanced technologies. InvertNet aims to develop improved semi-automated, high-throughput workflows for digitizing and providing access to invertebrate collections that balance the need for speed and cost-effectiveness with long-term preservation of specimens and accuracy of data capture. The proposed workflows build on recent methods for digitizing and providing access to high-quality images of multiple specimens (e.g., entire drawers of pinned insects) simultaneously. Limitations of previous approaches are discussed and possible solutions are proposed that incorporate advanced imaging and 3-D reconstruction technologies. InvertNet couples efficient digitization workflows with a highly robust network infrastructure capable of managing massive amounts of image data and related metadata and delivering high-quality images, including interactive 3-D reconstructions in real time via the Internet.