The Obama Administration's Cancer Moonshot: A Call for Proteomics.

Clin Cancer Res. 2016 May 19;

Authors: Conrads TP, Petricoin EF

Abstract
The Cancer Moonshot Program has been launched and represents a potentially paradigm-shifting initiative with the goal to implement a focused national effort to double the rate of progress against cancer. The placement of precision medicine, immunotherapy, genomics, and combination therapies was placed at the central nexus of this initiative. While we are extremely enthusiastic about the goals of the program, it is time we meet this revolutionary project with equally bold and cutting-edge ideas: its time we move firmly into the post-genome era and provide the necessary resources to propel and seize on innovative recent gains in the field of proteomics required for it to stand on equal footing in this narrative as a combined, synergistic engine for molecular profiling. After all, while the genome is the information archive, it is the proteins that actually do the work of the cell and represent the structural cellular machinery. It is the proteins that comprise most of the biomarkers that are measured to detect cancers, constitute the antigens that drive immune response and inter and itntracellular communications, and it is the proteins that are the drug targets for nearly every targeted therapy that is being evaluated in cancer trials today. We believe that a combined systems biology view of the tumor microenvironment that orients cancer studies back to the functional proteome, phosphoproteome and biochemistry of the cell will be essential to deliver on the promise of the Cancer Moonshot program.

PMID: 27199492 [PubMed - as supplied by publisher]

Reconstruction of gene regulatory networks reveals chromatin remodelers and key transcription factors in tumorigenesis.

Genome Med. 2016;8(1):57

Authors: Malysheva V, Mendoza-Parra MA, Saleem MA, Gronemeyer H

Abstract
BACKGROUND: Alterations in genetic and epigenetic landscapes are known to contribute to the development of different types of cancer. However, the mechanistic links between transcription factors and the epigenome which coordinate the deregulation of gene networks during cell transformation are largely unknown.
METHODS: We used an isogenic model of stepwise tumorigenic transformation of human primary cells to monitor the progressive deregulation of gene networks upon immortalization and oncogene-induced transformation. We applied a systems biology approach by combining transcriptome and epigenome data for each step during transformation and integrated transcription factor-target gene associations in order to reconstruct the gene regulatory networks that are at the basis of the transformation process.
RESULTS: We identified 142 transcription factors and 24 chromatin remodelers/modifiers (CRMs) which are preferentially associated with specific co-expression pathways that originate from deregulated gene programming during tumorigenesis. These transcription factors are involved in the regulation of divers processes, including cell differentiation, the immune response, and the establishment/modification of the epigenome. Unexpectedly, the analysis of chromatin state dynamics revealed patterns that distinguish groups of genes which are not only co-regulated but also functionally related. Decortication of transcription factor targets enabled us to define potential key regulators of cell transformation which are engaged in RNA metabolism and chromatin remodeling.
CONCLUSIONS: We reconstructed gene regulatory networks that reveal the alterations occurring during human cellular tumorigenesis. Using these networks we predicted and validated several transcription factors as key players for the establishment of tumorigenic traits of transformed cells. Our study suggests a direct implication of CRMs in oncogene-induced tumorigenesis and identifies new CRMs involved in this process. This is the first comprehensive view of the gene regulatory network that is altered during the process of stepwise human cellular tumorigenesis in a virtually isogenic system.

PMID: 27198694 [PubMed - in process]

Simple biophysics underpins collective conformations of the intrinsically disordered proteins of the Nuclear Pore Complex.

Elife. 2016;5

Authors: Vovk A, Gu C, Opferman MG, Kapinos LE, Lim RY, Coalson RD, Jasnow D, Zilman A

Abstract
Nuclear Pore Complexes (NPCs) are key cellular transporter that control nucleocytoplasmic transport in eukaryotic cells, but its transport mechanism is still not understood. The centerpiece of NPC transport is the assembly of intrinsically disordered polypeptides, known as FG nucleoporins, lining its passageway. Their conformations and collective dynamics during transport are difficult to assess in vivo. In vitro investigations provide partially conflicting results, lending support to different models of transport, which invoke various conformational transitions of the FG nucleoporins induced by the cargo-carrying transport proteins. We show that the spatial organization of FG nucleoporin assemblies with the transport proteins can be understood within a first principles biophysical model with a minimal number of key physical variables, such as the average protein interaction strengths and spatial densities. These results address some of the outstanding controversies and suggest how molecularly divergent NPCs in different species can perform essentially the same function.

PMID: 27198189 [PubMed - in process]

Metabolomics in cardiovascular diseases.

J Pharm Biomed Anal. 2015 Sep 10;113:121-36

Authors: Kordalewska M, Markuszewski MJ

Abstract
Cardiovascular diseases (CVDs) are the main cause of death globally. There is a need for the development of specific diagnostic methods, more effective therapeutic procedures as well as drugs, which can decrease the risk of deaths in the course of CVDs. For this reason, better understanding and explanation of molecular pathomechanisms of CVDs are essential. Metabolomics is focused on analysis of metabolites, small molecules which reflect the state of an organism in a certain point of time. Application of metabolomics approach in the investigation of molecular processes responsible for CVDs development may provide valuable information. In this article we overviewed recent reports employing application of untargeted and targeted metabolomic analyses in particular CVDs. Moreover, we focused on applications of various analytical platforms and metabolomics approaches which may contribute to the explanation of the pathomechanisms of different cardiovascular diseases.

PMID: 25958299 [PubMed - indexed for MEDLINE]

Metabolomics for laboratory diagnostics.

J Pharm Biomed Anal. 2015 Sep 10;113:108-20

Authors: Bujak R, Struck-Lewicka W, Markuszewski MJ, Kaliszan R

Abstract
Metabolomics is an emerging approach in a systems biology field. Due to continuous development in advanced analytical techniques and in bioinformatics, metabolomics has been extensively applied as a novel, holistic diagnostic tool in clinical and biomedical studies. Metabolome's measurement, as a chemical reflection of a current phenotype of a particular biological system, is nowadays frequently implemented to understand pathophysiological processes involved in disease progression as well as to search for new diagnostic or prognostic biomarkers of various organism's disorders. In this review, we discussed the research strategies and analytical platforms commonly applied in the metabolomics studies. The applications of the metabolomics in laboratory diagnostics in the last 5 years were also reviewed according to the type of biological sample used in the metabolome's analysis. We also discussed some limitations and further improvements which should be considered taking in mind potential applications of metabolomic research and practice.

PMID: 25577715 [PubMed - indexed for MEDLINE]

Genetic Approaches to Study Plant Responses to Environmental Stresses: An Overview.

Biology (Basel). 2016;5(2)

Authors: Moustafa K, Cross JM

Abstract
The assessment of gene expression levels is an important step toward elucidating gene functions temporally and spatially. Decades ago, typical studies were focusing on a few genes individually, whereas now researchers are able to examine whole genomes at once. The upgrade of throughput levels aided the introduction of systems biology approaches whereby cell functional networks can be scrutinized in their entireties to unravel potential functional interacting components. The birth of systems biology goes hand-in-hand with huge technological advancements and enables a fairly rapid detection of all transcripts in studied biological samples. Even so, earlier technologies that were restricted to probing single genes or a subset of genes still have their place in research laboratories. The objective here is to highlight key approaches used in gene expression analysis in plant responses to environmental stresses, or, more generally, any other condition of interest. Northern blots, RNase protection assays, and qPCR are described for their targeted detection of one or a few transcripts at a once. Differential display and serial analysis of gene expression represent non-targeted methods to evaluate expression changes of a significant number of gene transcripts. Finally, microarrays and RNA-seq (next-generation sequencing) contribute to the ultimate goal of identifying and quantifying all transcripts in a cell under conditions or stages of study. Recent examples of applications as well as principles, advantages, and drawbacks of each method are contrasted. We also suggest replacing the term "Next-Generation Sequencing (NGS)" with another less confusing synonym such as "RNA-seq", "high throughput sequencing", or "massively parallel sequencing" to avoid confusion with any future sequencing technologies.

PMID: 27196939 [PubMed - as supplied by publisher]

Revealing oxidative damage to enzymes of carbohydrate metabolism in yeast: An integration of 2D DIGE, quantitative proteomics and bioinformatics.

Proteomics. 2016 May 19;

Authors: Boone C, Grove R, Adamcova D, Braga C, Adamec J

Abstract
Clinical usage of lidocaine, a pro-oxidant has been linked with severe, mostly neurological complications. The mechanism(s) causing these complications is independent of the blockade of voltage gated sodium channels. The budding yeast S. cerevisiae lacks voltage gated sodium channels, thus provides an ideal system to investigate lidocaine induced protein and pathway alterations. Whole proteome alterations leading to these complications have not been identified. To address this S. cerevisiae was grown to stationary phase and exposed to an LC50 dose of lidocaine. The differential proteomes of lidocaine treatment and control were resolved six hours post exposure using 2D DIGE. Amine reactive dyes and carbonyl reactive dyes were used to assess protein abundance and protein oxidation, respectively. Quantitative analysis of these dyes ( ≥ 1.5-fold alteration, p ≤ 0.05 ) revealed a total of 33 proteoforms identified by mass spectrometry differing in abundance and/or oxidation upon lidocaine exposure. Network analysis showed enrichment of apoptotic proteins and cell wall maintenance proteins; while the abundance of proteins central to carbohydrate metabolism, such as triosephosphate isomerase and glyceraldehyde-3-phosphate dehydrogenase, and redox proteins superoxide dismutase and peroxiredoxin were significantly decreased. Enzymes of carbohydrate metabolism, such as phosphoglycerate kinase and enolase, the TCA cycle enzyme aconitase, and multiple ATP synthase subunits were found to be oxidatively modified. Also, the activity of aconitase was found to be decreased. Overall these data suggest that toxic doses of lidocaine induce significant disruption of glycolytic pathways, energy production, and redox balance potentially leading to cell malfunction and death. This article is protected by copyright. All rights reserved.

PMID: 27193513 [PubMed - as supplied by publisher]

Peptide-based systems analysis of inflammation induced myeloid-derived suppressor cells reveals diverse signaling pathways.

Proteomics. 2016 May 19;

Authors: Choksawangkarn W, Graham LM, Burke M, Lee SB, Ostrand-Rosenberg S, Fenselau C, Edwards NJ

Abstract
A better understanding of molecular signaling between myeloid-derived suppressor cells (MDSC), tumor cells, T-cells, and inflammatory mediators is expected to contribute to more effective cancer immunotherapies. We focus on plasma membrane associated proteins, which are critical in signaling and intercellular communication, and investigate changes in their abundance in MDSC of tumor-bearing mice subject to heightened versus basal inflammatory conditions. Using spectral counting, we observed statistically significant differential abundances for thirty-five proteins associated with the plasma membrane, most notably the pro-inflammatory proteins S100A8 and S100A9 which induce MDSC and promote their migration. We also tested whether the peptides associated with canonical pathways showed a statistically significant increase or decrease subject to heightened versus basal inflammatory conditions. Collectively, these studies used bottom-up proteomic analysis to identify plasma membrane associated pro-inflammatory molecules and pathways that drive MDSC accumulation, migration, and suppressive potency. This article is protected by copyright. All rights reserved.

PMID: 27193397 [PubMed - as supplied by publisher]

Minimum network constraint on reverse engineering to develop biological regulatory networks.

J Theor Biol. 2015 Sep 7;380:9-15

Authors: Shao B, Wu J, Tian B, Ouyang Q

Abstract
Reconstructing the topological structure of biological regulatory networks from microarray expression data or data of protein expression profiles is one of major tasks in systems biology. In recent years, various mathematical methods have been developed to meet this task. Here, based on our previously reported reverse engineering method, we propose a new constraint, i.e., the minimum network constraint, to facilitate the reconstruction of biological networks. Three well studied regulatory networks (the budding yeast cell cycle network, the fission yeast cell cycle network, and the SOS network of Escherichia coli) were used as the test sets to verify the performance of this method. Numerical results show that the biological networks prefer to use the minimal networks to fulfill their functional tasks, making it possible to apply minimal network criteria in the network reconstruction process. Two scenarios were considered in the reconstruction process: generating data using different initial conditions; and generating data from knock out and over-expression experiments. In both cases, network structures are revealed faithfully in a few steps using our approach.

PMID: 25981630 [PubMed - indexed for MEDLINE]

The fetal brain transcriptome and neonatal behavioral phenotype in the Ts1Cje mouse model of Down syndrome.

Am J Med Genet A. 2015 Sep;167A(9):1993-2008

Authors: Guedj F, Pennings JL, Ferres MA, Graham LC, Wick HC, Miczek KA, Slonim DK, Bianchi DW

Abstract
Human fetuses with Down syndrome demonstrate abnormal brain growth and reduced neurogenesis. Despite the prenatal onset of the phenotype, most therapeutic trials have been conducted in adults. Here, we present evidence for fetal brain molecular and neonatal behavioral alterations in the Ts1Cje mouse model of Down syndrome. Embryonic day 15.5 brain hemisphere RNA from Ts1Cje embryos (n = 5) and wild type littermates (n = 5) was processed and hybridized to mouse gene 1.0 ST arrays. Bioinformatic analyses were implemented to identify differential gene and pathway regulation during Ts1Cje fetal brain development. In separate experiments, the Fox scale, ultrasonic vocalization and homing tests were used to investigate behavioral deficits in Ts1Cje pups (n = 29) versus WT littermates (n = 64) at postnatal days 3-21. Ts1Cje fetal brains displayed more differentially regulated genes (n = 71) than adult (n = 31) when compared to their age-matched euploid brains. Ts1Cje embryonic brains showed up-regulation of cell cycle markers and down-regulation of the solute-carrier amino acid transporters. Several cellular processes were dysregulated at both stages, including apoptosis, inflammation, Jak/Stat signaling, G-protein signaling, and oxidoreductase activity. In addition, early behavioral deficits in surface righting, cliff aversion, negative geotaxis, forelimb grasp, ultrasonic vocalization, and the homing tests were observed. The Ts1Cje mouse model exhibits abnormal gene expression during fetal brain development, and significant neonatal behavioral deficits in the pre-weaning period. In combination with human studies, this suggests that the Down syndrome phenotype manifests prenatally and provides a rationale for prenatal therapy to improve perinatal brain development and postnatal neurocognition.

PMID: 25975229 [PubMed - indexed for MEDLINE]

Mathematical modelling of the diurnal regulation of the MEP pathway in Arabidopsis.

New Phytol. 2015 May;206(3):1075-85

Authors: Pokhilko A, Bou-Torrent J, Pulido P, Rodríguez-Concepción M, Ebenhöh O

Abstract
Isoprenoid molecules are essential elements of plant metabolism. Many important plant isoprenoids, such as chlorophylls, carotenoids, tocopherols, prenylated quinones and hormones are synthesised in chloroplasts via the 2-C-methyl-d-erythritol 4-phosphate (MEP) pathway. Here we develop a mathematical model of diurnal regulation of the MEP pathway in Arabidopsis thaliana. We used both experimental and theoretical approaches to integrate mechanisms potentially involved in the diurnal control of the pathway. Our data show that flux through the MEP pathway is accelerated in light due to the photosynthesis-dependent supply of metabolic substrates of the pathway and the transcriptional regulation of key biosynthetic genes by the circadian clock. We also demonstrate that feedback regulation of both the activity and the abundance of the first enzyme of the MEP pathway (1-deoxy-D-xylulose 5-phosphate synthase, DXS) by pathway products stabilizes the flux against changes in substrate supply and adjusts the flux according to product demand under normal growth conditions. These data illustrate the central relevance of photosynthesis, the circadian clock and feedback control of DXS for the diurnal regulation of the MEP pathway.

PMID: 25598499 [PubMed - indexed for MEDLINE]

Advancing our understanding of infant bronchiolitis through phenotyping and endotyping: Clinical and molecular approaches.

Expert Rev Respir Med. 2016 May 18;

Authors: Hasegawa K, Dumas O, Hartert TV, Camargo CA

Abstract
INTRODUCTION: Bronchiolitis is a major public health problem worldwide. However, no effective treatment strategies are available, other than supportive care. Areas Covered: Although bronchiolitis has been considered a single disease diagnosed based on clinical characteristics, emerging evidence supports both clinical and pathobiological heterogeneity. The characterization of this heterogeneity supports the concept that bronchiolitis consists of multiple phenotypes or consistent grouping of characteristics. Expert Commentary: Using unbiased statistical approaches, multidimentional clinical characteristics will derive bronchiolitis phenotypes. Furthermore, molecular and systems biology approaches will, by linking pathobiology to phenotype, identify endotypes. Large cohort studies of bronchiolitis with comprehensive clinical characterization and system-wide profiling of the "-omics" data (e.g., host genome, transcriptome, epigenome, viral genome, microbiome, metabolome) should enhance our ability to molecularly understand these phenotypes and lead to more targeted and personalized approaches to bronchiolitis treatment.

PMID: 27192374 [PubMed - as supplied by publisher]

Practical aspects of NGS-based pathways analysis for personalized cancer science and medicine.

Oncotarget. 2016 May 14;

Authors: Kotelnikova EA, Pyatnitskiy M, Paleeva A, Kremenetskaya O, Vinogradov D

Abstract
Nowadays, the personalized approach to health care and cancer care in particular is becoming more and more popular and is taking an important place in the translational medicine paradigm. In some cases, detection of the patient-specific individual mutations that point to a targeted therapy has already become a routine practice for clinical oncologists. Wider panels of genetic markers are also on the market which cover a greater number of possible oncogenes including those with lower reliability of resulting medical conclusions. In light of the large availability of high-throughput technologies, it is very tempting to use complete patient-specific New Generation Sequencing (NGS) or other "omics" data for cancer treatment guidance. However, there are still no gold standard methods and protocols to evaluate them. Here we will discuss the clinical utility of each of the data types and describe a systems biology approach adapted for single patient measurements. We will try to summarize the current state of the field focusing on the clinically relevant case-studies and practical aspects of data processing.

PMID: 27191992 [PubMed - as supplied by publisher]

22 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Systems Biology"[Title/Abstract] AND ("2005/01/01"[PDAT] : "3000"[PDAT])

These pubmed results were generated on 2016/05/18

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Computational Systems Biology Approach Predicts Regulators and Targets of microRNAs and Their Genomic Hotspots in Apoptosis Process.

Mol Biotechnol. 2016 May 13;

Authors: Alanazi IO, Ebrahimie E

Abstract
Novel computational systems biology tools such as common targets analysis, common regulators analysis, pathway discovery, and transcriptomic-based hotspot discovery provide new opportunities in understanding of apoptosis molecular mechanisms. In this study, after measuring the global contribution of microRNAs in the course of apoptosis by Affymetrix platform, systems biology tools were utilized to obtain a comprehensive view on the role of microRNAs in apoptosis process. Network analysis and pathway discovery highlighted the crosstalk between transcription factors and microRNAs in apoptosis. Within the transcription factors, PRDM1 showed the highest upregulation during the course of apoptosis, with more than 9-fold expression increase compared to non-apoptotic condition. Within the microRNAs, MIR1208 showed the highest expression in non-apoptotic condition and downregulated by more than 6 fold during apoptosis. Common regulators algorithm showed that TNF receptor is the key upstream regulator with a high number of regulatory interactions with the differentially expressed microRNAs. BCL2 and AKT1 were the key downstream targets of differentially expressed microRNAs. Enrichment analysis of the genomic locations of differentially expressed microRNAs led us to the discovery of chromosome bands which were highly enriched (p < 0.01) with the apoptosis-related microRNAs, such as 13q31.3, 19p13.13, and Xq27.3 This study opens a new avenue in understanding regulatory mechanisms and downstream functions in the course of apoptosis as well as distinguishing genomic-enriched hotspots for apoptosis process.

PMID: 27178576 [PubMed - as supplied by publisher]

A heuristic model for working memory deficit in schizophrenia.

Biochim Biophys Acta. 2016 May 10;

Authors: Qi Z, Yu GP, Tretter F, Pogarell O, Grace AA, Voit EO

Abstract
BACKGROUND: The life of schizophrenia patients is severely affected deficits in working memory. In various brain regions, the reciprocal interactions between excitatory glutamatergic neurons and inhibitory GABAergic neurons are crucial. Other neurotransmitters, in particular dopamine, serotonin, acetylcholine, and norepinephrine, modulate the local balance between glutamate and GABA and therefore regulate the function of brain regions. Persistent alterations in the balances between the neurotransmitters can result in working memory deficits.
METHODS: Here we present a heuristic computational model that accounts for interactions among neurotransmitters across various brain regions. The model is based on the concept of a neurochemical interaction matrix at the biochemical level and combines this matrix with a mobile model representing physiological dynamic balances among neurotransmitter systems associated with working memory.
RESULTS: The comparison of clinical and simulation results demonstrates that the model output is qualitatively very consistent with the available data. In addition, the model captured how perturbations migrated through different neurotransmitters and brain regions. Results showed that chronic administration of ketamine can cause a variety of imbalances, and application of an antagonist of the D2 receptor in PFC can also induce imbalances but in a very different manner.
CONCLUSIONS: The heuristic computational model permits a variety of assessments of genetic, biochemical, and pharmacological perturbations and serves as an intuitive tool for explaining clinical and biological observations.
GENERAL SIGNIFICANCE: The heuristic model is more intuitive than biophysically detailed models. It can serve as an important tool for interdisciplinary communication and even for psychiatric education of patients and relatives. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

PMID: 27177811 [PubMed - as supplied by publisher]

Systems Medicine approaches to improving understanding, treatment, and clinical management of Neuroendocrine Prostate Cancer.

Curr Pharm Des. 2016 May 13;

Authors: Yadav KK, Khader S, Readhead B, Yadav SS, Li L, Kasarksis A, Tewari AK, Dudley JT

Abstract
BACKGROUND: Prostate cancer is the most commonly diagnosed cancer in men. More than 200,000 new cases are added each year in the US, translating to a lifetime risk of 1 in 7 men. Neuroendocrine prostate cancer (NEPC) is an aggressive and treatment-resistant form of prostate cancer. A subset of patients treated with aggressive androgen deprivation therapy (ADT) present with NEPC. Patients with NEPC have a reduced 5-year overall survival rate of 12.6%. Knowledge integration from genetic, epigenetic, biochemical and therapeutic studies suggests NEPC as an indicative mechanism of resistance development to various forms of therapy.
METHODS: In this perspective, we discuss various experimental, computational and risk prediction methodologies that can be utilized to identify novel therapies against NEPC. We reviewed literature from PubMed using key terms, and computationally analyzed publicly available genomics data to present different possibilities for developing systems medicine based therapeutic and curative models to understand and target prostate cancer and specifically NEPC.
RESULTS: Our study includes gene-set analyses, network analyses, genomics and phenomics aided drug development, microRNA and peptide-based therapeutics, pathway modeling, drug repositioning and cancer immunotherapies. We also discuss the application of cancer risk estimations and mining of electronic medical records to develop personalized risk predictions models for NEPC. Preemptive stratification of patients who are at risk of evolving NEPC phenotypes using predictive models could also help to design and deliver better therapies.
CONCLUSIONS: Collectively, understanding the mechanism of NEPC evolution from prostate cancer using systems biology approaches would help in devising better treatment strategies and is critical and unmet clinical need.

PMID: 27174811 [PubMed - as supplied by publisher]

Editorial overview: Systems biology-the intersection of experiments and computation, underpinning biotechnology.

Curr Opin Biotechnol. 2016 May 9;

Authors: Styczynski MP, Theis FJ

PMID: 27173375 [PubMed - as supplied by publisher]

MicroRNAs in the Evaluation and Potential Treatment of Liver Diseases.

J Clin Med. 2016;5(5)

Authors: Mahgoub A, Steer CJ

Abstract
Acute and chronic liver disease continue to result in significant morbidity and mortality of patients, along with increasing burden on their families, society and the health care system. This in part is due to increased incidence of liver disease associated factors such as metabolic syndrome; improved survival of patients with chronic predisposing conditions such as HIV; as well as advances in the field of transplantation and associated care leading to improved survival. The fact that one disease can result in different manifestations and outcomes highlights the need for improved understanding of not just genetic phenomenon predisposing to a condition, but additionally the role of epigenetic and environmental factors leading to the phenotype of the disease. It is not surprising that providers continue to face daily challenges pertaining to diagnostic accuracy, prognostication of disease severity, progression, and response to therapies. A number of these challenges can be addressed by incorporating a personalized approach of management to the current paradigm of care. Recent advances in the fields of molecular biology and genetics have paved the way to more accurate, individualized and precise approach to caring for liver disease. The study of microRNAs and their role in both healthy and diseased livers is one example of such advances. As these small, non-coding RNAs work on fine-tuning of cellular activities and organ function in a dynamic and precise fashion, they provide us a golden opportunity to advance the field of hepatology. The study of microRNAs in liver disease promises tremendous improvement in hepatology and is likely to lay the foundation towards a personalized approach in liver disease.

PMID: 27171116 [PubMed]

Brain Radiation Information Data Exchange (BRIDE): integration of experimental data from low-dose ionising radiation research for pathway discovery.

BMC Bioinformatics. 2016;17(1):212

Authors: Karapiperis C, Kempf SJ, Quintens R, Azimzadeh O, Vidal VL, Pazzaglia S, Bazyka D, Mastroberardino PG, Scouras ZG, Tapio S, Benotmane MA, Ouzounis CA

Abstract
BACKGROUND: The underlying molecular processes representing stress responses to low-dose ionising radiation (LDIR) in mammals are just beginning to be understood. In particular, LDIR effects on the brain and their possible association with neurodegenerative disease are currently being explored using omics technologies.
RESULTS: We describe a light-weight approach for the storage, analysis and distribution of relevant LDIR omics datasets. The data integration platform, called BRIDE, contains information from the literature as well as experimental information from transcriptomics and proteomics studies. It deploys a hybrid, distributed solution using both local storage and cloud technology.
CONCLUSIONS: BRIDE can act as a knowledge broker for LDIR researchers, to facilitate molecular research on the systems biology of LDIR response in mammals. Its flexible design can capture a range of experimental information for genomics, epigenomics, transcriptomics, and proteomics. The data collection is available at: <bride.azurewebsites.net>.

PMID: 27170263 [PubMed - in process]