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.

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.

SIMULATION OF ION CONDUCTION IN α-HEMOLYSIN NANOPORES WITH COVALENTLY ATTACHED ß-CYCLODEXTRIN BASED ON BOLTZMANN TRANSPORT MONTE CARLO MODEL.

Ion channels, as natures' solution to regulating biological environments, are particularly interesting to device engineers seeking to understand how natural molecular systems realize device-like functions, such as stochastic sensing of organic analytes. What's more, attaching molecular adaptors in desired orientations inside genetically engineered ion channels, enhances the system functionality as a biosensor. In general, a hierarchy of simulation methodologies is needed to study different aspects of a biological system like ion channels. Biology Monte Carlo (BioMOCA), a three-dimensional coarse-grained particle ion channel simulator, offers a powerful and general approach to study ion channel permeation. BioMOCA is based on the Boltzmann Transport Monte Carlo (BTMC) and Particle-Particle-Particle-Mesh (P(3)M) methodologies developed at the University of Illinois at Urbana-Champaign. In this paper, we have employed BioMOCA to study two engineered mutations of α-HL, namely (M113F)(6)(M113C-D8RL2)(1)-ß-CD and (M113N)(6)(T117C-D8RL3)(1)-ß-CD. The channel conductance calculated by BioMOCA is slightly higher than experimental values. Permanent charge distributions and the geometrical shape of the channels gives rise to selectivity towards anions and also an asymmetry in I-V curves, promoting a rectification largely for cations.

Reduced thermal conductivity in nanoengineered rough Ge and GaAs nanowires.

We model and compare the thermal conductivity of rough semiconductor nanowires (NWs) of Si, Ge, and GaAs for thermoelectric devices. On the basis of full phonon dispersion relations, the effect of NW surface roughness on thermal conductivity is derived from perturbation theory and appears as an efficient way to scatter phonons in Si, Ge, and GaAs NWs with diameter D < 200 nm. For small diameters and large root-mean-square roughness Delta, thermal conductivity is limited by surface asperities and varies quadratically as (D/Delta)(2). At room temperature, our model previously agreed with experimental observations of thermal conductivity down to 2 W m(-1) K(-1) in rough 56 nm Si NWs with Delta = 3 nm. In comparison to Si, we predict here remarkably low thermal conductivity in Ge and GaAs NWs of 0.1 and 0.4 W m(-1) K(-1), respectively, at similar roughness and diameter.

Single-channel current through nicotinic receptor produced by closure of binding site C-loop.

We investigated the initial coupling of agonist binding to channel gating of the nicotinic acetylcholine receptor using targeted molecular-dynamics (TMD) simulation. After TMD simulation to accelerate closure of the C-loops at the agonist binding sites, the region of the pore that passes through the cell membrane expands. To determine whether the structural changes in the pore result in ion conduction, we used a coarse-grained ion conduction simulator, Biology Boltzmann transport Monte Carlo, and applied it to two structural frames taken before and after TMD simulation. The structural model before TMD simulation represents the channel in the proposed "resting" state, whereas the model after TMD simulation represents the channel in the proposed "active" state. Under external voltage biases, the channel in the "active" state was permeable to cations. Our simulated ion conductance approaches that obtained experimentally and recapitulates several functional properties characteristic of the nicotinic acetylcholine receptor. Thus, closure of the C-loop triggers a structural change in the channel sufficient to account for the open channel current. This approach of applying Biology Boltzmann transport Monte Carlo simulation can be used to further investigate the binding to gating transduction mechanism and the structural bases for ion selection and translocation.

Impact of phonon-surface roughness scattering on thermal conductivity of thin si nanowires.

We present a novel approach for computing the surface roughness-limited thermal conductivity of silicon nanowires with diameter D<100 nm. A frequency-dependent phonon scattering rate is computed from perturbation theory and related to a description of the surface through the root-mean-square roughness height Delta and autocovariance length L. Using a full phonon dispersion relation, we find a quadratic dependence of thermal conductivity on diameter and roughness as (D/Delta)(2). Computed results show excellent agreement with experimental data for a wide diameter and temperature range (25-350 K), and successfully predict the extraordinarily low thermal conductivity of 2 W m(-1) K-1 at room temperature in rough-etched 50 nm silicon nanowires.

Simulation of charge transport in ion channels and nanopores with anisotropic permittivity.

Ion channels are part of nature's solution for regulating biological environments. Every ion channel consists of a chain of amino acids carrying a strong and sharply varying permanent charge, folded in such a way that it creates a nanoscopic aqueous pore spanning the otherwise mostly impermeable membranes of biological cells. These naturally occurring proteins are particularly interesting to device engineers seeking to understand how such nanoscale systems realize device-like functions. Availability of high-resolution structural information from X-ray crystallography, as well as large-scale computational resources, makes it possible to conduct realistic ion channel simulations. In general, a hierarchy of simulation methodologies is needed to study different aspects of a biological system like ion channels. Biology Monte Carlo (BioMOCA), a three-dimensional coarse-grained particle ion channel simulator, offers a powerful and general approach to study ion channel permeation. BioMOCA is based on the Boltzmann Transport Monte Carlo (BTMC) and Particle-Particle-Particle-Mesh (P(3)M) methodologies developed at the University of Illinois at Urbana-Champaign. In this paper we briefly discuss the various approaches to simulating ion flow in channel systems that are currently being pursued by the biophysics and engineering communities, and present the effect of having anisotropic dielectric constants on ion flow through a number of nanopores with different effective diameters.

Electrostatic properties of the mechanosensitive channel of small conductance MscS.

The mechanosensitive channel of small conductance (MscS) belongs to a family of membrane proteins that are gated in response to changes in membrane tension, thereby protecting the cell from hypo-osmotic shock. Here we report on passive ion transport simulations of MscS in a POPC bilayer using a coarse-grained particle-based description based on the Boltzmann transport Monte Carlo method. Single channel current-voltage curves are computed over hundreds of nanoseconds for channel conformations derived from all-atom molecular dynamics simulations reaching an overall simulation time of over 5 micros. Channel conformations similar to that of the crystal structure exhibit low conductance, whereas conformations reached after opening the channel by means of steered molecular dynamics simulations match experimentally determined conductances. However, while experiments indicate a slight preference for anionic currents, the simulated channel strongly selects anions over cations and the direction of rectification at high voltages is opposite to what is observed in experiments. Three-dimensional maps of time-averaged ion distribution and equilibrium occupancy profiles constructed from trajectory data indicate separation of anions and cations inside and in the immediate vicinity of the large cytoplasmic domain of MscS, in accordance with earlier molecular dynamics simulations. This separation arises from the distribution of ionizable residues of MscS and suggests a specific, yet unknown, functional purpose.

Ion-nanotube terahertz oscillator.

We report the intriguing dynamics of a potassium ion interacting with a 16 A carbon nanotube. The ion induces a strong dielectric response in the nanotube wall that can be described through a self-consistent tight-binding method. The polarization of the nanotube was found to play a critical role in the ion-nanotube interaction, which exhibits a low access barrier of only 1.05 kcal/mol and a deep, attractive well with a depth of about 30 kcal/mol. An ion bound in the nanotube is predicted to oscillate at a frequency of about 0.4 terahertz, dragging the electrons of the nanotube along. Besides its appealing nature in low-dimensional physics, such a nano-oscillator may serve as a room temperature terahertz wave detector.

Empirical nanotube model for biological applications.

An empirical model is developed to capture the electrostatics of finite-length single-walled armchair carbon nanotubes for biological applications. Atomic partial charges are determined to match the electrostatic potential field computed at the B3LYP/6-31G* level of density functional theory, and a tight-binding Hamiltonian is selected which permits one to reproduce the dielectric properties in good agreement with density functional theory results. The new description is applied to study movement of a water molecule through a finite-length nanotube channel in order to demonstrate the method's feasibility. We find that atomic partial charges on the tube edges dominate the interaction between the nanotube and the entering water molecule, while the polarization of the nanotube lowers the electrostatic energy of the water molecule inside the tube.

Screening of Water Dipoles Inside Finite-Length Armchair Carbon Nanotubes.

The electronic structure and dielectric screening of finite-length armchair carbon nanotubes are studied with both tight-binding and ab initio methods. Good agreement is found in the band gap oscillation patterns and dielectric constants, which validates the tight-binding method as a reliable and fast approach to describe the screening effect of carbon nanotubes. For an illustration, our method is applied to a system consisting of a short (6,6) nanotube filled with six water molecules. Substantial screening of the water dipoles through the nanotube is observed. This polarization effect should have an important influence on the permeation of water and other biomolecules inside carbon nanotubes.