Ultra-sensitive label-free in-situ detection of dynamically driven self-assembly of 2D nanoplatelets on SOI chip

Fluid dispersed two-dimensional (2D) composite materials with dynamically tunable functional properties have recently emerged as a novel highly promising class of optoelectronic materials, opening up new routes not only for the emerging field of metamaterials but also to chip-scale multifunctional metadevices. However, in-situ monitoring and detection of the dynamic ordering of 2D nanoparticles on chip and during the device operation is still a huge challenge. Here we introduce a novel approach for on-chip, in-situ Raman characterisation of 2D-fluid composite materials incorporated into Si photonics chip. In this work the Raman signal for 2D nanoplatelets is selectively enhanced by Fabry-Perot resonator design of CMOS photonic-compatible microfluidic channels. This has then been extended to demonstrate the first in-situ Raman detection of the dynamics of individual 2D nanoplatelets, within a microfluidic channel. Our work paves the way for the first practicable realisation of 3D photonic microstructure shaping based on 2D-fluid composites and CMOS photonics platform.We acknowledge financial support from: the Engineering and Physical Sciences Research Council (EPSRC) of the United Kingdom via the EPSRC Centre for Doctoral Training in Electromagnetic Metamaterials (Grant No. EP/L015331/1) and also via Grants No. EP/G036101/1, EP/M002438/1, and EP/M001024/1, Science Foundation Ireland Grant No. 12/IA/1300, the Ministry of Education and Science of the Russian Federation (Grant No. 14.B25.31.0002) and the Royal Society International Exchange Grant 2015/R3. The microfluidic structures were fabricated at Tyndall National Institute under the Science Foundation Ireland NAP368 and NAP94 programmes

ModEx: a general purpose computer model exploration system

We present a general purpose visual analysis system that can be used for exploring parameters of a variety of computer models. Our proposed system offers key components of a visual parameter analysis framework including parameter sampling, deriving output summaries, and an exploration interface. It also provides an API for rapid development of parameter space exploration solutions as well as the flexibility to support custom workflows for different application domains. We evaluate the effectiveness of our system by demonstrating it in three domains: data mining, machine learning and specific application in bioinformatics

Dynamic in-situ sensing of fluid-dispersed 2D materials integrated on microfluidic Si chip

This is the author accepted manuscript. The final version is available from Nature Publishing Group via the DOI in this record.The supplementary videos associated with this article are located in ORE at: https://doi.org/10.24378/exe.1643In this work, we propose a novel approach for wafer-scale integration of 2D materials on CMOS photonics chip utilising methods of synthetic chemistry and microfluidics technology. We have successfully demonstrated that this approach can be used for integration of any fluid-dispersed 2D nano-objects on silicon-on-insulator photonics platform. We demonstrate for the first time that the design of an optofluidic waveguide system can be optimised to enable simultaneous in-situ Raman spectroscopy monitoring of 2D dispersed flakes during the device operation. Moreover, for the first time, we have successfully demonstrated the possibility of label-free 2D flake detection via selective enhancement of the Stokes Raman signal at specific wavelengths. We discovered an ultra-high signal sensitivity to the xyz alignment of 2D flakes within the optofluidic waveguide, which in turn enables precise in-situ alignment detection for the first practicable realisation of 3D photonic microstructure shaping based on 2D-fluid composites and CMOS photonics platform while also representing a useful technological tool for the control of liquid phase deposition of 2D materials.We acknowledge financial support from: The Engineering and Physical Sciences Research Council (EPSRC) of the United Kingdom via the EPSRC Centre for Doctoral Training in Electromagnetic Metamaterials (Grant No. EP/L015331/1) and also via Grant Nos. EP/N035569/1, EP/G036101/1, EP/M002438/1, and EP/M001024/1, Science Foundation Ireland Grant No. 12/IA/1300, the Ministry of Education and Science of the Russian Federation (Grant No. 14.B25.31.0002) and the Royal Society International Exchange Grant 2015/R3. The microfluidic structures were fabricated at Tyndall National Institute under the Science Foundation Ireland NAP368 and NAP94 programs

Spark: A navigational paradigm for genomic data exploration

Biologists possess the detailed knowledge critical for extracting biological insight from genome-wide data resources, and yet they are increasingly faced with nontrivial computational analysis challenges posed by genome-scale methodologies. To lower this computational barrier, particularly in the early data exploration phases, we have developed an interactive pattern discovery and visualization approach, Spark, designed with epigenomic data in mind. Here we demonstrate Spark's ability to reveal both known and novel epigenetic signatures, including a previously unappreciated binding association between the YY1 transcription factor and the corepressor CTBP2 in human embryonic stem cells

G9a regulates group 2 innate lymphoid cell development by repressing the group 3 innate lymphoid cell program.

Innate lymphoid cells (ILCs) are emerging as important regulators of homeostatic and disease-associated immune processes. Despite recent advances in defining the molecular pathways that control development and function of ILCs, the epigenetic mechanisms that regulate ILC biology are unknown. Here, we identify a role for the lysine methyltransferase G9a in regulating ILC2 development and function. Mice with a hematopoietic cell-specific deletion of G9a (Vav.G9a(-/-) mice) have a severe reduction in ILC2s in peripheral sites, associated with impaired development of immature ILC2s in the bone marrow. Accordingly, Vav.G9a(-/-) mice are resistant to the development of allergic lung inflammation. G9a-dependent dimethylation of histone 3 lysine 9 (H3K9me2) is a repressive histone mark that is associated with gene silencing. Genome-wide expression analysis demonstrated that the absence of G9a led to increased expression of ILC3-associated genes in developing ILC2 populations. Further, we found high levels of G9a-dependent H3K9me2 at ILC3-specific genetic loci, demonstrating that G9a-mediated repression of ILC3-associated genes is critical for the optimal development of ILC2s. Together, these results provide the first identification of an epigenetic regulatory mechanism in ILC development and function

NucTools: analysis of chromatin feature occupancy profiles from high-throughput sequencing data

Background: Biomedical applications of high-throughput sequencing methods generate a vast amount of data in which numerous chromatin features are mapped along the genome. The results are frequently analysed by creating binary data sets that link the presence/absence of a given feature to specific genomic loci. However, the nucleosome occupancy or chromatin accessibility landscape is essentially continuous. It is currently a challenge in the field to cope with continuous distributions of deep sequencing chromatin readouts and to integrate the different types of discrete chromatin features to reveal linkages between them. Results: Here we introduce the NucTools suite of Perl scripts as well as MATLAB- and R-based visualization programs for a nucleosome-centred downstream analysis of deep sequencing data. NucTools accounts for the continuous distribution of nucleosome occupancy. It allows calculations of nucleosome occupancy profiles averaged over several replicates, comparisons of nucleosome occupancy landscapes between different experimental conditions, and the estimation of the changes of integral chromatin properties such as the nucleosome repeat length. Furthermore, NucTools facilitates the annotation of nucleosome occupancy with other chromatin features like binding of transcription factors or architectural proteins, and epigenetic marks like histone modifications or DNA methylation. The applications of NucTools are demonstrated for the comparison of several datasets for nucleosome occupancy in mouse embryonic stem cells (ESCs) and mouse embryonic fibroblasts (MEFs). Conclusions: The typical workflows of data processing and integrative analysis with NucTools reveal information on the interplay of nucleosome positioning with other features such as for example binding of a transcription factor CTCF, regions with stable and unstable nucleosomes, and domains of large organized chromatin K9me2 modifications (LOCKs). As potential limitations and problems we discuss how inter-replicate variability of MNase-seq experiments can be addressed

VisR: An interactive visualization framework for analysis of sequencing data

Several tools have been developed to enable biologists to perform initial browsing and exploration of sequencing data. However, the computational tool set for further analyses often requires significant computational expertise to use and many of the biologists with the knowledge needed to interpret these data must rely on programming experts. In this thesis, we focus on addressing this limitation through visualization tools for exploratory analysis of sequencing data and contribute the design and development of two novel systems that are flexible enough to allow a high degree of analysis power, while at the same time are easy to use for non-programmers: (1) a general purpose framework that bridges the gap between the biologists and the bioinformaticians through a system of visual analysis modules that can be rapidly developed and connected together, and (2) a first-of-its-kind system that facilitates visual parameter space analysis for a wide variety of computer models. We start by providing a characterization of the data and an abstraction of the domain tasks in the field of epigenetics and present a design study on development and evaluation of ChAsE, an interactive tool to facilitate analysis and visualization of epigenetic datasets. We will then discuss VisR, a general framework for analysis of sequencing datasets that provides both a computationally rich as well as accessible framework for integrative and interactive analyses through modules called R-apps that utilize packages in R and repositories such as Bioconductor. Our framework provides means for interactive exploration of the results or the R-apps, and supports linking apps to create more complex workflows. It also provides an ecosystem to allow extension and sharing of the apps. We finally present ModEx, a general purpose system for exploring parameters of a variety of computer models. We discuss how the system offers key components of visual parameter space analysis frameworks including parameter sampling, deriving output summaries, and an interactive and customizable exploration interface and explain how it can be used for rapid development of custom solutions for different application domains

Visualization of large scale volumetric datasets

In this thesis, we address the problem of large-scale data visualization from two aspects, dimensionality and resolution. We introduce a novel data structure called Differential Time- Histogram Table (DTHT) for visualization of time-varying (4D) scalar data. The proposed data structure takes advantage of the coherence in time-varying datasets and allows efficient updates of data necessary for rendering during data exploration and visualization while guaranteeing that the scalar field visualized is within a given error tolerance of the scalar field sampled. To address the high-resolution datasets, we propose a hierarchical data structure and introduce a novel hybrid framework to improve the quality of multi-resolution visualization. For more accurate rendering at coarser levels of detail, we reduce aliasing artifacts by approximating data distribution with a Gaussian basis at each level of detail and we reduce blurring by using transparent isosurfaces to capture high-frequency features usually missed in coarse resolution renderings

Visualization of Time-Varying Volumetric Data using Differential Time-Histogram Table

We introduce a novel data structure called Differential Time-Histogram Table (DTHT) for visualization of timevarying scalar data. This data structure only stores voxels that are changing between time-steps or during transfer function updates. It allows efficient updates of data necessary for rendering during a sequence of queries common during data exploration and visualization. The table is used to update the values held in memory so that efficient visualization is supported while guaranteeing that the scalar field visualized is within a given error tolerance of the scalar field sampled. Our data structure allows updates of time-steps in the order of tens of frames per second for volumes of sizes of 4.5GB, enabling real-time time-sliders