Machine Learning and Integrative Analysis of Biomedical Big Data.

Recent developments in high-throughput technologies have accelerated the accumulation of massive amounts of omics data from multiple sources: genome, epigenome, transcriptome, proteome, metabolome, etc. Traditionally, data from each source (e.g., genome) is analyzed in isolation using statistical and machine learning (ML) methods. Integrative analysis of multi-omics and clinical data is key to new biomedical discoveries and advancements in precision medicine. However, data integration poses new computational challenges as well as exacerbates the ones associated with single-omics studies. Specialized computational approaches are required to effectively and efficiently perform integrative analysis of biomedical data acquired from diverse modalities. In this review, we discuss state-of-the-art ML-based approaches for tackling five specific computational challenges associated with integrative analysis: curse of dimensionality, data heterogeneity, missing data, class imbalance and scalability issues

Associations with photoreceptor thickness measures in the UK Biobank.

Spectral-domain OCT (SD-OCT) provides high resolution images enabling identification of individual retinal layers. We included 32,923 participants aged 40-69 years old from UK Biobank. Questionnaires, physical examination, and eye examination including SD-OCT imaging were performed. SD OCT measured photoreceptor layer thickness includes photoreceptor layer thickness: inner nuclear layer-retinal pigment epithelium (INL-RPE) and the specific sublayers of the photoreceptor: inner nuclear layer-external limiting membrane (INL-ELM); external limiting membrane-inner segment outer segment (ELM-ISOS); and inner segment outer segment-retinal pigment epithelium (ISOS-RPE). In multivariate regression models, the total average INL-RPE was observed to be thinner in older aged, females, Black ethnicity, smokers, participants with higher systolic blood pressure, more negative refractive error, lower IOPcc and lower corneal hysteresis. The overall INL-ELM, ELM-ISOS and ISOS-RPE thickness was significantly associated with sex and race. Total average of INL-ELM thickness was additionally associated with age and refractive error, while ELM-ISOS was additionally associated with age, smoking status, SBP and refractive error; and ISOS-RPE was additionally associated with smoking status, IOPcc and corneal hysteresis. Hence, we found novel associations of ethnicity, smoking, systolic blood pressure, refraction, IOPcc and corneal hysteresis with photoreceptor thickness

EFRC Bulletin 76 January 2005. With technical Updates from the Organic Advisory Service

The regular report from Elm Farm Research Centre - the Organic Research Centre in the UK - covering its own research and information and that of other relevant issue

Modeling Virus-Host Networks

Virus-host interactions are being cataloged at an increasing rate using protein interaction assays and small interfering RNA screens for host factors necessary for infection. These interactions can be viewed as a network, where genes or proteins are nodes, and edges correspond to associations between them. Virus-host interac- tion networks will eventually support the study and treatment of infection, but first require more data and better analysis techniques. This dissertation targets these goals with three aims. The first aim tackles the lack of data by providing a method for the computational prediction of virus-host protein interactions. We show that HIV-human protein interactions can be predicted using documented human peptide motifs found to be conserved on HIV proteins from different subtypes. We find that human proteins predicted to bind to HIV proteins are enriched in both documented HIV targeted proteins and pathways known to be utilized by HIV. The second aim seeks to improve peptide motif annotation on virus proteins, starting with the dock- ing site for protein kinases ERK1 and ERK2, which phosphorylate HIV proteins during infection. We find that the docking site motif, in spite of being suggestive of phosphorylation, is not present on all HIV subtypes for some HIV proteins, and we provide evidence that two variations of the docking site motif could explain phos- phorylation. In the third aim, we analyze virus-host networks and build on the observation that viruses target host hub proteins. We show that of the two hub types, date and party, HIV and influenza virus proteins prefer to interact with the latter. The methods presented here for prediction and motif refinement, as well as the analysis of virus targeted hubs, provide a useful set of tools and hypotheses for the study of virus-host interactions

Genetic Modification of Inherited Retinopathy in Mice

The retina, as a critical component of the sensory system, consists of multiple cell types, of which, photoreceptors play a key role in receiving, integrating and transmitting light signals. The biofunctions of photoreceptors rely on their proper growth and development, which is predominantly governed by a cluster of molecules that comprise the transcriptional regulation for photoreceptor development. Any disruption of these molecules potentially incurs retinal pathologies. It is known that deficiencies of nuclear receptor subfamily 2 group E member 3 (NR2E3) or neural retina leucine-zipper (NRL), two molecules in regulating photoreceptor cell development, cause photoreceptor dysplasia. In a sensitized chemical mutagenesis study to identify genetic modifiers in retinal degeneration (rd) 7 mice (Nr2e3rd7), Tvrm222, was established, in which photoreceptor dysplasia was significantly rescued compared to that in Nr2e3rd7 mutants. Notably, the Tvrm222 allele also ameliorates photoreceptor dysplasia in Nrl knockout mice. According to whole-genome mapping and exome sequencing, the modifier was localized to Chromosome 6 and was identified as a missense variant in the FERM domain containing 4B (Frmd4b) gene, which is predicted to cause the substitution of serine residue 938 with proline (S938P). Furthermore, we observed that the Frmd4bTvrm222 allele preserved the integrity of the fragmented external limiting membrane (ELM) present in both rd7 and Nrl–/– mouse retinas. FRMD4B, as a binding partner of cytohesin 3 (CYTH3), has been proposed to participate in cell junction remodeling. However, its function in ELM maintenance and photoreceptor dysplasia has not been previously examined. This study revealed that the S938P variation significantly reduces in vitro membrane recruitment of FRMD4B. Notably, in an attempt to explore the molecular mechanisms underlying the modifying effect of FRMD4B938P on dysplastic retinas, we observed an increased activation of ADP-ribosylation factor 6, a direct substrate for CYTH3, both in vitro and in vivo, as well as decreased phosphorylation of AKT in Tvrm222 retinas. These changes were accompanied by an elevation in cell membrane-associated zonula adherens and occludens proteins in Tvrm222 retinas. Taken together, this study determines a critical role of FRMD4B in maintaining the integrity of adhesive support (at the ELM) and in rescuing photoreceptor dysplasia in mice

Probabilistic and artificial intelligence modelling of drought and agricultural crop yield in Pakistan

Pakistan is a drought-prone, agricultural nation with hydro-meteorological imbalances that increase the scarcity of water resources, thus, constraining water availability and leading major risks to the agricultural productivity sector and food security. Rainfall and drought are imperative matters of consideration, both for hydrological and agricultural applications. The aim of this doctoral thesis is to advance new knowledge in designing hybridized probabilistic and artificial intelligence forecasts models for rainfall, drought and crop yield within the agricultural hubs in Pakistan. The choice of these study regions is a strategic decision, to focus on precision agriculture given the importance of rainfall and drought events on agricultural crops in socioeconomic activities of Pakistan. The outcomes of this PhD contribute to efficient modelling of seasonal rainfall, drought and crop yield to assist farmers and other stakeholders to promote more strategic decisions for better management of climate risk for agriculturalreliant nations

Systematic analysis of somatic mutations driving cancer: Uncovering functional protein regions in disease development

Background: Recent advances in sequencing technologies enable the large-scale identification of genes that are affected by various genetic alterations in cancer. However, understanding tumor development requires insights into how these changes cause altered protein function and impaired network regulation in general and/or in specific cancer types. Results: In this work we present a novel method called iSiMPRe that identifies regions that are significantly enriched in somatic mutations and short in-frame insertions or deletions (indels). Applying this unbiased method to the complete human proteome, by using data enriched through various cancer genome projects, we identified around 500 protein regions which could be linked to one or more of 27 distinct cancer types. These regions covered the majority of known cancer genes, surprisingly even tumor suppressors. Additionally, iSiMPRe also identified novel genes and regions that have not yet been associated with cancer. Conclusions: While local somatic mutations correspond to only a subset of genetic variations that can lead to cancer, our systematic analyses revealed that they represent an accompanying feature of most cancer driver genes regardless of the primary mechanism by which they are perturbed during tumorigenesis. These results indicate that the accumulation of local somatic mutations can be used to pinpoint genes responsible for cancer formation and can also help to understand the effect of cancer mutations at the level of functional modules in a broad range of cancer driver genes. Reviewers: This article was reviewed by Sándor Pongor, Michael Gromiha and Zoltán Gáspári. © 2016 Mészáros et al

Resting-state, responsivity, and circadian rhythmicity: three different functional components of autonomic nervous system activity in the context of developmental psychopathology

First onset of psychiatric symptoms and disorders usually occurs in childhood or adolescence, presenting a significant portion of the burden of disease in young individuals. The disruption of physiological regulatory systems may present one patho-mechanism underlying the development of psychiatric symptoms and disorders in this age group. Altered autonomic nervous system (ANS) function has been shown to occur prior to observable clinical symptoms, and is typically characterized by an imbalance between its two branches, the sympathetic and parasympathetic nervous systems. Dysfunction of the ANS is frequently indexed by reduced vagally-mediated resting-state heart rate variability (vmHRV), reflecting parasympathetic (vagal) activity. Substantial neurophysiological evidence suggests a relationship between reduced vmHRV and psychiatric disorders characterized by impaired emotion regulation (ER). Alongside resting-state ANS activity, measures of ANS responsivity to challenge (i.e., cardiac reactivity and recovery in response and subsequent to psychological stress exposure) have been suggested as markers of ER, while existing findings on the respective relationships are mixed. Markers of cardiac vagal activity follow rhythmic pattern of circadian variation (circadian variation patterns, CVP), reaching peak levels during nighttime. Indices of CVP of ANS activity may quantify restorative physiological processes, and may be linked with the restoration of autonomic balance. CVP of ANS activity may therefore present further indices of socio-emotional regulatory capacity. The aim of the present thesis was to investigate different markers of cardiac autonomic activity indexing different functional components of ANS activity (i.e., resting-state, responsivity, and circadian rhythmicity) in developmental psychopathology. First, potential associations between experiences of severe adversity early in life (early life maltreatment, ELM), typically associated with deficient ER, and resting-state vmHRV were investigated in a comprehensive meta-analysis. Second, cardiac responsivity to a standardized stress task was assessed as potential predictor of treatment outcome over two years in a preliminary experimental psychotherapy study. Here, heart-rate (HR) and vmHRV responsivity were used as ANS markers. In a third study, CVP of cardiac autonomic activity was analyzed in female adolescents engaging in non-suicidal self-injury (NSSI). The meta-analytic study suggested no general association between resting-state vmHRV and ELM exposure, while accompanying meta-regression analyses revealed potential patterns of association between exposure to ELM and resting-state vmHRV as a function of several moderators, including mean age of and presence of psychopathology in the respective study sample. In the second study, resting-state and vmHRV recovery following stress exposure were identified as potential predictors of clinical improvement over the time course of two years in adolescent females with higher and lower dimensional manifestations of BPD. The third study revealed altered CVP of ANS activity in NSSI disorder compared to healthy controls, and in association with more severe ELM exposure, and critical confounders of the respective associations were identified. The present synopsis aims to integrate these findings into a psychophysiological framework of ER in development, and discuss methodological considerations, limitations, and potential future directions resulting from the studies that constitute the thesis at hand