Visualizing Biological Membrane Organization and Dynamics

International audienc

MinOmics, an Integrative and Immersive Tool for Multi-Omics Analysis

International audienceProteomic and transcriptomic technologies resulted in massive biological datasets, their interpretation requiring sophisticated computational strategies. Efficient and intuitive real-time analysis remains challenging. We use proteomic data on 1417 proteins of the green microalga Chlamydomonas reinhardtii to investigate physicochemical parameters governing selectivity of three cysteine-based redox post translational modifications (PTM): glutathionylation (SSG), nitrosylation (SNO) and disulphide bonds (SS) reduced by thioredoxins. We aim to understand underlying molecular mechanisms and structural determinants through integration of redox proteome data from gene- to structural level. Our interactive visual analytics approach on an 8.3 m2 display wall of 25 MPixel resolution features stereoscopic three dimensions (3D) representation performed by UnityMol WebGL. Virtual reality headsets complement the range of usage configurations for fully immersive tasks. Our experiments confirm that fast access to a rich cross-linked database is necessary for immersive analysis of structural data. We emphasize the possibility to display complex data structures and relationships in 3D, intrinsic to molecular structure visualization, but less common for omics-network analysis. Our setup is powered by MinOmics, an integrated analysis pipeline and visualization framework dedicated to multi-omics analysis. MinOmics integrates data from various sources into a materialized physical repository. We evaluate its performance, a design criterion for the framework

MinOmics, an Integrative and Immersive Tool for Multi-Omics Analysis

Proteomic and transcriptomic technologies resulted in massive biological datasets, their interpretation requiring sophisticated computational strategies. Efficient and intuitive real-time analysis remains challenging. We use proteomic data on 1417 proteins of the green microalga Chlamydomonas reinhardtii to investigate physicochemical parameters governing selectivity of three cysteine-based redox post translational modifications (PTM): glutathionylation (SSG), nitrosylation (SNO) and disulphide bonds (SS) reduced by thioredoxins. We aim to understand underlying molecular mechanisms and structural determinants through integration of redox proteome data from gene- to structural level. Our interactive visual analytics approach on an 8.3 m2 display wall of 25 MPixel resolution features stereoscopic three dimensions (3D) representation performed by UnityMol WebGL. Virtual reality headsets complement the range of usage configurations for fully immersive tasks. Our experiments confirm that fast access to a rich cross-linked database is necessary for immersive analysis of structural data. We emphasize the possibility to display complex data structures and relationships in 3D, intrinsic to molecular structure visualization, but less common for omics-network analysis. Our setup is powered by MinOmics, an integrated analysis pipeline and visualization framework dedicated to multi-omics analysis. MinOmics integrates data from various sources into a materialized physical repository. We evaluate its performance, a design criterion for the framework

Immersive analytics for oncology patient cohorts

This thesis proposes a novel interactive immersive analytics tool and methods to interrogate the cancer patient cohort in an immersive virtual environment, namely Virtual Reality to Observe Oncology data Models (VROOM). The overall objective is to develop an immersive analytics platform, which includes a data analytics pipeline from raw gene expression data to immersive visualisation on virtual and augmented reality platforms utilising a game engine. Unity3D has been used to implement the visualisation. Work in this thesis could provide oncologists and clinicians with an interactive visualisation and visual analytics platform that helps them to drive their analysis in treatment efficacy and achieve the goal of evidence-based personalised medicine. The thesis integrates the latest discovery and development in cancer patients’ prognoses, immersive technologies, machine learning, decision support system and interactive visualisation to form an immersive analytics platform of complex genomic data. For this thesis, the experimental paradigm that will be followed is in understanding transcriptomics in cancer samples. This thesis specifically investigates gene expression data to determine the biological similarity revealed by the patient's tumour samples' transcriptomic profiles revealing the active genes in different patients. In summary, the thesis contributes to i) a novel immersive analytics platform for patient cohort data interrogation in similarity space where the similarity space is based on the patient's biological and genomic similarity; ii) an effective immersive environment optimisation design based on the usability study of exocentric and egocentric visualisation, audio and sound design optimisation; iii) an integration of trusted and familiar 2D biomedical visual analytics methods into the immersive environment; iv) novel use of the game theory as the decision-making system engine to help the analytics process, and application of the optimal transport theory in missing data imputation to ensure the preservation of data distribution; and v) case studies to showcase the real-world application of the visualisation and its effectiveness

An evaluation of immersive virtual tours for curriculum innovation and engagement in higher education

The COVID-19 pandemic has placed unique pressures on higher education and exposed problems in remote delivery of captivating learning experiences into the future as the sector adapts to a post-pandemic “normal”. Field trips and facility visits have had to take a back seat during this period; as a result, the ability of academics to deliver object-based and visual-spatial learning was compromised. There is a lack of tested, approachable workflows for production of meaningful immersive tools that can temporarily replace and later augment in-person lessons. Virtual reality remains an unconvincing pedagogical tool, though low immersion flat-screen delivered virtual experiences are already considered pedagogically valuable. This thesis evaluates the use of low immersion virtual tours for higher education during the pandemic, primarily in the context of undergraduate biomedical science. A panoramic virtual tour of the Chau Chak Wing Museum was constructed in 3D Vista Virtual Tour Pro software and used to facilitate object-based for first year medical science students (n = 59). Structural equation modelling was used to discern technology acceptance. The tour was edited for a postgraduate business studies cohort and structural equation modelling was again conducted with a larger cohort (n = 163). Additionally, a virtual tour of the National Biocontainment K7b facility at Westmead Hospital was constructed for the purpose of remote education and familiarisation of staff and visitors. Lastly, technologies for creation and annotation/presentation of immersive three-dimensional anatomy and physiology models are assessed. We compare polygonal modelling, photogrammetry, and medical image segmentation in generation of geometry, and virtual tours, game engines and online tools for presentation of geometry. We found that virtual tours are a highly approachable, affordable, and adaptable solution for delivery of immersive learning experiences. Reception from students and academics alike was highly positive. Significant utility of virtually delivered object-based learning experiences is presented. Ultimately, we identify virtual tours as a means for provision of purposeful immersive learning that is complementary to in-person experiences. Innovation and implementation of virtual experiences will continue into the post-pandemic period, to facilitate useful “pre-work” tasks that maximise the benefit of in-person lessons