Systems analysis of protective immune responses to RTS,S malaria vaccination in humans.

Proc Natl Acad Sci U S A. 2017 Feb 13;:

Authors: Kazmin D, Nakaya HI, Lee EK, Johnson MJ, van der Most R, van den Berg RA, Ballou WR, Jongert E, Wille-Reece U, Ockenhouse C, Aderem A, Zak DE, Sadoff J, Hendriks J, Wrammert J, Ahmed R, Pulendran B

Abstract
RTS,S is an advanced malaria vaccine candidate and confers significant protection against Plasmodium falciparum infection in humans. Little is known about the molecular mechanisms driving vaccine immunity. Here, we applied a systems biology approach to study immune responses in subjects receiving three consecutive immunizations with RTS,S (RRR), or in those receiving two immunizations of RTS,S/AS01 following a primary immunization with adenovirus 35 (Ad35) (ARR) vector expressing circumsporozoite protein. Subsequent controlled human malaria challenge (CHMI) of the vaccinees with Plasmodium-infected mosquitoes, 3 wk after the final immunization, resulted in ∼50% protection in both groups of vaccinees. Circumsporozoite protein (CSP)-specific antibody titers, prechallenge, were associated with protection in the RRR group. In contrast, ARR-induced lower antibody responses, and protection was associated with polyfunctional CD4(+) T-cell responses 2 wk after priming with Ad35. Molecular signatures of B and plasma cells detected in PBMCs were highly correlated with antibody titers prechallenge and protection in the RRR cohort. In contrast, early signatures of innate immunity and dendritic cell activation were highly associated with protection in the ARR cohort. For both vaccine regimens, natural killer (NK) cell signatures negatively correlated with and predicted protection. These results suggest that protective immunity against P. falciparum can be achieved via multiple mechanisms and highlight the utility of systems approaches in defining molecular correlates of protection to vaccination.

PMID: 28193898 [PubMed - as supplied by publisher]

A combined model reduction algorithm for controlled biochemical systems.

BMC Syst Biol. 2017 Feb 13;11(1):17

Authors: Snowden TJ, van der Graaf PH, Tindall MJ

Abstract
BACKGROUND: Systems Biology continues to produce increasingly large models of complex biochemical reaction networks. In applications requiring, for example, parameter estimation, the use of agent-based modelling approaches, or real-time simulation, this growing model complexity can present a significant hurdle. Often, however, not all portions of a model are of equal interest in a given setting. In such situations methods of model reduction offer one possible approach for addressing the issue of complexity by seeking to eliminate those portions of a pathway that can be shown to have the least effect upon the properties of interest.
METHODS: In this paper a model reduction algorithm bringing together the complementary aspects of proper lumping and empirical balanced truncation is presented. Additional contributions include the development of a criterion for the selection of state-variable elimination via conservation analysis and use of an 'averaged' lumping inverse. This combined algorithm is highly automatable and of particular applicability in the context of 'controlled' biochemical networks.
RESULTS: The algorithm is demonstrated here via application to two examples; an 11 dimensional model of bacterial chemotaxis in Escherichia coli and a 99 dimensional model of extracellular regulatory kinase activation (ERK) mediated via the epidermal growth factor (EGF) and nerve growth factor (NGF) receptor pathways. In the case of the chemotaxis model the algorithm was able to reduce the model to 2 state-variables producing a maximal relative error between the dynamics of the original and reduced models of only 2.8% whilst yielding a 26 fold speed up in simulation time. For the ERK activation model the algorithm was able to reduce the system to 7 state-variables, incurring a maximal relative error of 4.8%, and producing an approximately 10 fold speed up in the rate of simulation. Indices of controllability and observability are additionally developed and demonstrated throughout the paper. These provide insight into the relative importance of individual reactants in mediating a biochemical system's input-output response even for highly complex networks.
CONCLUSIONS: Through application, this paper demonstrates that combined model reduction methods can produce a significant simplification of complex Systems Biology models whilst retaining a high degree of predictive accuracy. In particular, it is shown that by combining the methods of proper lumping and empirical balanced truncation it is often possible to produce more accurate reductions than can be obtained by the use of either method in isolation.

PMID: 28193218 [PubMed - in process]

Sm-p80-based schistosomiasis vaccine mediated epistatic interactions identified potential immune signatures for vaccine efficacy in mice and baboons.

PLoS One. 2017;12(2):e0171677

Authors: Rojo JU, Melkus MW, Kottapalli KR, Okiya OE, Sudduth J, Zhang W, Molehin AJ, Carter D, Siddiqui AA

Abstract
Schistosomiasis is a neglected parasitic disease of major public health concern as it affects over 250 million people in developing countries. Currently there is no licensed vaccine available against schistosomiasis. The Schistosoma mansoni calpain protein, Sm-p80, is a leading vaccine candidate now ready to move to clinical trials. In order to better assess Sm-p80 vaccine immunogenicity; here we used a systems biology approach employing RNA-sequencing to identify gene signatures and epistatic interactions following Sm-p80 vaccination in mouse and baboon models that may predict vaccine efficacy. Recombinant Sm-p80 + CpG-oligodeoxynucleotide (ODN) vaccine formulation induced both cellular and humoral immunity genes with a predominant TH1 response as well as TH2 and TH17 gene signatures. Early gene responses and gene-network interactions in mice immunized with rSm-p80 + ODN appear to be initiated through TLR4 signaling. CSF genes, S100A alarmin genes and TNFRSF genes appear to be a signature of vaccine immunogenicity/efficacy as identified by their participation in gene network interactions in both mice and baboons. These gene families may provide a basis for predicting desirable outcomes for vaccines against schistosomiasis leading to a better understanding of the immune system response to vaccination.

PMID: 28192534 [PubMed - in process]

Molecular networks related to the immune system and mitochondria are targets for the pesticide dieldrin in the zebrafish (Danio rerio) central nervous system.

J Proteomics. 2017 Feb 09;:

Authors: Cowie AM, Sarty KI, Mercer A, Koh J, Kidd KA, Martyniuk CJ

Abstract
The objectives of this study were to determine the behavioral and molecular responses in the adult zebrafish (Danio rerio) central nervous system (CNS) following a dietary exposure to the pesticide dieldrin. Zebrafish were fed pellets spiked with 0.03, 0.15, or 1.8μg/g dieldrin for 21days. Behavioral analysis revealed no difference in exploratory behaviors or those related to anxiety. Transcriptional networks for T-cell aggregation and selection were decreased in expression suggesting an immunosuppressive effect of dieldrin, consistent with other studies investigating organochlorine pesticides. Processes related to oxidative phosphorylation were also differentially affected by dieldrin. Quantitative proteomics (iTRAQ) using a hybrid quadrupole-Orbitrap identified 226 proteins that were different in abundance in one or more doses. These included ATP synthase subunits (mitochondrial) and hypoxia up-regulated protein 1 which were decreased and NADH dehydrogenases (mitochondrial) and signal recognition particle 9 which were up-regulated. Thus, proteins affected were functionally associated with the mitochondria and a network implicated PD and Huntington's disease as those associated with proteins. Molecular networks related to mitochondrial dysfunction and T-cell regulation are hypothesized to underlie the association between dieldrin and PD. These data contribute to a comprehensive transcriptomic and proteomic biomarker framework for pesticide exposures and neurodegenerative diseases.
BIOLOGICAL SIGNIFICANCE: Dieldrin is a persistent organochlorine pesticide that has been associated with human neurodegenerative disease such as Parkinson's disease. Dieldrin is ranked 18th on the 2015 U.S. Agency for Toxic Substances and Disease Registry and continues to be a pesticide of concern for human health. Transcriptomics and quantitative proteomics (ITRAQ) were employed to characterize the molecular networks in the central nervous system that are altered with dietary exposure to dieldrin. We found that transcriptional and protein networks related to the immune system, mitochondria, and Parkinson's disease were preferentially affected by dieldrin. The study provides new insight into the mechanisms of dieldrin neurotoxicity that may explain, in part, the association between this pesticide and increased risks to neurodegeneration. These data contribute in a significant way to developing a molecular framework for pesticide induced neurotoxicity.

PMID: 28192238 [PubMed - as supplied by publisher]

Designer nanoparticle: nanobiotechnology tool for cell biology.

Nano Converg. 2016;3(1):22

Authors: Thimiri Govinda Raj DB, Khan NA

Abstract
This article discusses the use of nanotechnology for subcellular compartment isolation and its application towards subcellular omics. This technology review significantly contributes to our understanding on use of nanotechnology for subcellular systems biology. Here we elaborate nanobiotechnology approach of using superparamagnetic nanoparticles (SPMNPs) optimized with different surface coatings for subcellular organelle isolation. Using pulse-chase approach, we review that SPMNPs interacted differently with the cell depending on its surface functionalization. The article focuses on the use of functionalized-SPMNPs as a nanobiotechnology tool to isolate high quality (both purity and yield) plasma membranes and endosomes or lysosomes. Such nanobiotechnology tool can be applied in generating subcellular compartment inventories. As a future perspective, this strategy could be applied in areas such as immunology, cancer and stem cell research.

PMID: 28191432 [PubMed - in process]

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

SIAM J Sci Comput. 2016;38(3):C179-C202

Authors: Drawert B, Trogdon M, Toor S, Petzold L, Hellander A

Abstract
Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

PMID: 28190948 [PubMed - in process]

Anesthesia, Brain Changes, and Behavior: Insights from Neural Systems Biology.

Prog Neurobiol. 2017 Feb 08;:

Authors: Colon E, Bittner EA, Kussman B, McCann ME, Soriano S, Borsook D

Abstract
Long-term consequences of anesthetic exposure in humans are not well understood. It is possible that alterations in brain function occur beyond the initial anesthetic administration. Research in children and adults has reported cognitive and/or behavioral changes after surgery and general anesthesia that may be short lived in some patients, while in others, such changes may persist. The changes observed in humans are corroborated by a large body of evidence from animal studies that support a role for alterations in neuronal survival (neuroapoptosis) or structure (altered dendritic and glial morphology) and later behavioral deficits at older age after exposure to various anesthetic agents during fetal or early life. The potential of anesthetics to induce long-term alterations in brain function, particularly in vulnerable populations, warrants investigation. In this review, we critically evaluate the available preclinical and clinical data on the developing and aging brain, and in known vulnerable populations to provide insights into potential changes that may affect the general population of patients in a more, subtle manner. In addition this review summarizes underlying processes of how general anesthetics produce changes in the brain at the cellular and systems level and the current understanding underlying mechanisms of anesthetics agents on brain systems. Finally, we present how neuroimaging techniques currently emerge as promising approaches to evaluate and define changes in brain function resulting from anesthesia, both in the short and the long-term.

PMID: 28189740 [PubMed - as supplied by publisher]

Quantitative Map of β-Lactone-Induced Virulence Regulation.

J Proteome Res. 2017 Feb 10;:

Authors: Krysiak J, Stahl M, Vomacka J, Fetzer C, Lakemeyer M, Fux A, Sieber SA

Abstract
β-Lactones have recently been introduced as the first selective ClpP inhibitors that attenuate virulence of both sensitive Staphylococcus aureus and multiresistant strains (MRSA). Although previous knockout studies showed that ClpP is essential for S. aureus alpha-toxin production, a link between β-lactone inhibition and molecular virulence mechanisms has been lacking so far. We here perform a chemical-proteomic approach to elucidate antivirulence pathways. First, we demonstrate by gel-free activity-based protein profiling that ClpP is the predominant target of β-lactones. Only a few off-targets were discovered, which, unlike ClpP, were not involved in the reduction of alpha-toxin expression. Second, in-depth mechanistic insight was provided by a full proteomic comparison between lactone treated and untreated S. aureus cells. Quantitative mass-spectrometric analysis revealed increased repressor of toxin (Rot) levels and a corresponding down-regulation of α-toxin, providing the first direct connection between the lactone-dependent phenotype and a corresponding cellular mechanism. By building up a quantitative virulence regulation network, we visualize the impact of ClpP inhibition in a systems biology context. Interestingly, a lack of in vitro Rot degradation by either ClpXP or ClpCP calls either for a proteolysis mechanism with yet unknown adaptor proteins or for an indirect mode of action that may involve ClpX-mediated RNA signaling and feedback circuits.

PMID: 28186774 [PubMed - as supplied by publisher]

Combinatorial bZIP dimers define complex DNA-binding specificity landscapes.

Elife. 2017 Feb 10;6:

Authors: Rodriguez-Martinez JA, Reinke AW, Bhimsaria D, Keating AE, Ansari AZ

Abstract
How transcription factor dimerization impacts DNA binding specificity is poorly understood. Guided by protein dimerization properties, we examined DNA binding specificities of 270 human bZIP pairs. DNA interactomes of 80 heterodimers and 22 homodimers revealed that 72% of heterodimer motifs correspond to conjoined half-sites preferred by partnering monomers. Remarkably, the remaining motifs are composed of variably-spaced half-sites (12%) or 'emergent' sites (16%) that cannot be readily inferred from half-site preferences of partnering monomers. These binding sites were biochemically validated by EMSA-FRET analysis and validated in vivo by ChIP-seq data from human cell lines. Focusing on ATF3, we observed distinct cognate site preferences conferred by different bZIP partners, and demonstrated that genome-wide binding of ATF3 is best explained by considering many dimers in which it participates. Importantly, our compendium of bZIP-DNA interactomes predicted bZIP binding to 156 disease associated SNPs, of which only 20 were previously annotated with known bZIP motifs.

PMID: 28186491 [PubMed - as supplied by publisher]

Understanding the mTOR signaling pathway via mathematical modeling.

Wiley Interdiscip Rev Syst Biol Med. 2017 Feb 10;:

Authors: Sulaimanov N, Klose M, Busch H, Boerries M

Abstract
The mechanistic target of rapamycin (mTOR) is a central regulatory pathway that integrates a variety of environmental cues to control cellular growth and homeostasis by intricate molecular feedbacks. In spite of extensive knowledge about its components, the molecular understanding of how these function together in space and time remains poor and there is a need for Systems Biology approaches to perform systematic analyses. In this work, we review the recent progress how the combined efforts of mathematical models and quantitative experiments shed new light on our understanding of the mTOR signaling pathway. In particular, we discuss the modeling concepts applied in mTOR signaling, the role of multiple feedbacks and the crosstalk mechanisms of mTOR with other signaling pathways. We also discuss the contribution of principles from information and network theory that have been successfully applied in dissecting design principles of the mTOR signaling network. We finally propose to classify the mTOR models in terms of the time scale and network complexity, and outline the importance of the classification toward the development of highly comprehensive and predictive models. For further resources related to this article, please visit the WIREs website.

PMID: 28186392 [PubMed - as supplied by publisher]

Algal Cell Response to Pulsed Waved Stimulation and Its Application to Increase Algal Lipid Production.

Sci Rep. 2017 Feb 10;7:42003

Authors: Savchenko O, Xing J, Yang X, Gu Q, Shaheen M, Huang M, Yu X, Burrell R, Patra P, Chen J

Abstract
Generating renewable energy while sequestering CO2 using algae has recently attracted significant research attention, mostly directing towards biological methods such as systems biology, genetic engineering and bio-refining for optimizing algae strains. Other approaches focus on chemical screening to adjust culture conditions or culture media. We report for the first time the physiological changes of algal cells in response to a novel form of mechanical stimulation, or a pulsed wave at the frequency of 1.5 MHz and the duty cycle of 20%. We studied how the pulsed wave can further increase algal lipid production on top of existing biological and chemical methods. Two commonly used algal strains, fresh-water Chlorella vulgaris and seawater Tetraselmis chuii, were selected. We have performed the tests in shake flasks and 1 L spinner-flask bioreactors. Conventional Gravimetric measurements show that up to 20% increase for algal lipid could be achieved after 8 days of stimulation. The total electricity cost needed for the stimulations in a one-liter bioreactor is only one-tenth of a US penny. Gas liquid chromatography shows that the fatty acid composition remains unchanged after pulsed-wave stimulation. Scanning electron microscope results also suggest that pulsed wave stimulation induces shear stress and thus increases algal lipid production.

PMID: 28186124 [PubMed - in process]

Later Age at Onset of Independent Walking Is Associated with Lower Bone Strength at Fracture-Prone Sites in Older Men.

J Bone Miner Res. 2017 Feb 09;:

Authors: Ireland A, Muthuri S, Rittweger J, Adams JE, Ward KA, Kuh D, Cooper R

Abstract
Later age at onset of independent walking is associated with lower leg bone strength in childhood and adolescence. However it is unknown whether these associations persist into older age, or whether they are evident at axial (central) or upper limb sites. Therefore we examined walking age obtained at 2y and bone outcomes obtained by dual-energy X-ray absorptiometry (DXA) and peripheral quantitative computed tomography (pQCT) scans at 60-64y in a nationally-representative cohort study of British people, the MRC National Survey of Health and Development. It was hypothesised that later walking age would be associated with lower bone strength at all sites. Later independent walking age was associated with lower height-adjusted hip (standardised regression coefficients with 95%CI) [-0.179(-0.251,-0.107)], spine [-0.157(-0.232,-0.082)] and distal radius [-0.159(-0.245,-0.073)] bone mineral content (BMC, indicating bone compressive strength) in men (all P < 0.001). Adjustment for covariates partially attenuated these associations, primarily due to lower lean mass and adolescent sporting ability in later walkers. These associations were also evident for a number of hip geometric parameters (including cross-sectional moment of inertia (CSMI), indicating bone bending/torsional strength) assessed by Hip Structural Analysis (HSA) from DXA scans. Similar height-adjusted associations were also observed in women for several hip, spine and upper limb outcomes, although adjustment for fat or lean mass led to complete attenuation for most outcomes, with the exception of femoral shaft CSMI and spine bone area (BA). In conclusion, later independent walking age appears to have a lifelong association with bone strength across multiple skeletal sites in men. These effects may result from direct effects of early life loading on bone growth, and mediation by adult body composition. Results suggest that late walking age may represent a novel risk factor for subsequent low bone strength. Existing interventions effective in hastening walking age may have positive effects on bone across life. This article is protected by copyright. All rights reserved.

PMID: 28181695 [PubMed - as supplied by publisher]

Cellular Signaling Pathways in Insulin Resistance-Systems Biology Analyses of Microarray Dataset Reveals New Drug Target Gene Signatures of Type 2 Diabetes Mellitus.

Front Physiol. 2017;8:13

Authors: Muhammad SA, Raza W, Nguyen T, Bai B, Wu X, Chen J

Abstract
Purpose: Type 2 diabetes mellitus (T2DM) is a chronic and metabolic disorder affecting large set of population of the world. To widen the scope of understanding of genetic causes of this disease, we performed interactive and toxicogenomic based systems biology study to find potential T2DM related genes after cDNA differential analysis. Methods: From the list of 50-differential expressed genes (p < 0.05), we found 9-T2DM related genes using extensive data mapping. In our constructed gene-network, T2DM-related differentially expressed seeder genes (9-genes) are found to interact with functionally related gene signatures (31-genes). The genetic interaction network of both T2DM-associated seeder as well as signature genes generally relates well with the disease condition based on toxicogenomic and data curation. Results: These networks showed significant enrichment of insulin signaling, insulin secretion and other T2DM-related pathways including JAK-STAT, MAPK, TGF, Toll-like receptor, p53 and mTOR, adipocytokine, FOXO, PPAR, P13-AKT, and triglyceride metabolic pathways. We found some enriched pathways that are common in different conditions. We recognized 11-signaling pathways as a connecting link between gene signatures in insulin resistance and T2DM. Notably, in the drug-gene network, the interacting genes showed significant overlap with 13-FDA approved and few non-approved drugs. This study demonstrates the value of systems genetics for identifying 18 potential genes associated with T2DM that are probable drug targets. Conclusions: This integrative and network based approaches for finding variants in genomic data expect to accelerate identification of new drug target molecules for different diseases and can speed up drug discovery outcomes.

PMID: 28179884 [PubMed - in process]

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

"Systems Biology"[Title/Abstract]

These pubmed results were generated on 2017/02/09

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

"Systems Biology"[Title/Abstract]

These pubmed results were generated on 2017/02/06

PubMed comprises more than millions of 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.

Make Precision Medicine Work for Chronic Kidney Disease.

Med Princ Pract. 2016 Dec 14;:

Authors: Sun L, Zou LX, Chen MJ

Abstract
Precision medicine is based on accurate diagnosis and tailored intervention through the use of omics and clinical data together with epidemiology and environmental exposures. Precision medicine should be achieved with minimum adverse events and maximum efficacy in patients with chronic kidney disease (CKD). In this review, the breakthroughs of omics in CKD and the application of systems biology are reviewed. The potential role of transforming growth factor-β1 in the targeted intervention of renal fibrosis is discussed as an example of how to make precision medicine work for CKD.

PMID: 28152529 [PubMed - as supplied by publisher]

Bioinformatics Analysis of Functional Associations of PTMs.

Methods Mol Biol. 2017;1558:303-320

Authors: Minguez P, Bork P

Abstract
Post-translational modifications (PTMs) are an important source of protein regulation; they fine-tune the function, localization, and interaction with other molecules of the majority of proteins and are partially responsible for their multifunctionality. Usually, proteins have several potential modification sites, and their patterns of occupancy are associated with certain functional states. These patterns imply cross talk among PTMs within and between proteins, the majority of which are still to be discovered. Several methods detect associations between PTMs; these have recently combined into a global resource, the PTMcode database, which contains already known and predicted functional associations between pairs of PTMs from more than 45,000 proteins in 19 eukaryotic species.

PMID: 28150244 [PubMed - in process]

Prediction of Protein Interactions by Structural Matching: Prediction of PPI Networks and the Effects of Mutations on PPIs that Combines Sequence and Structural Information.

Methods Mol Biol. 2017;1558:255-270

Authors: Tuncbag N, Keskin O, Nussinov R, Gursoy A

Abstract
Structural details of protein interactions are invaluable to the understanding of cellular processes. However, the identification of interactions at atomic resolution is a continuing challenge in the systems biology era. Although the number of structurally resolved complexes in the Protein Databank increases exponentially, the complexes only cover a small portion of the known structural interactome. In this chapter, we review the PRISM system that is a protein-protein interaction (PPI) prediction tool-its rationale, principles, and applications. We further discuss its extensions to discover the effect of single residue mutations, to model large protein assemblies, to improve its performance by exploiting conformational protein ensembles, and to reconstruct large PPI networks or pathway maps.

PMID: 28150242 [PubMed - in process]

Bioinformatics Analysis of Protein Phosphorylation in Plant Systems Biology Using P3DB.

Methods Mol Biol. 2017;1558:127-138

Authors: Yao Q, Xu D

Abstract
Protein phosphorylation is one of the most pervasive protein post-translational modification events in plant cells. It is involved in many plant biological processes, such as plant growth, organ development, and plant immunology, by regulating or switching signaling and metabolic pathways. High-throughput experimental methods like mass spectrometry can easily characterize hundreds to thousands of phosphorylation events in a single experiment. With the increasing volume of the data sets, Plant Protein Phosphorylation DataBase (P3DB, http://p3db.org ) provides a comprehensive, systematic, and interactive online platform to deposit, query, analyze, and visualize these phosphorylation events in many plant species. It stores the protein phosphorylation sites in the context of identified mass spectra, phosphopeptides, and phosphoproteins contributed from various plant proteome studies. In addition, P3DB associates these plant phosphorylation sites to protein physicochemical information in the protein charts and tertiary structures, while various protein annotations from hierarchical kinase phosphatase families, protein domains, and gene ontology are also added into the database. P3DB not only provides rich information, but also interconnects and provides visualization of the data in networks, in systems biology context. Currently, P3DB includes the KiC (Kinase Client) assay network, the protein-protein interaction network, the kinase-substrate network, the phosphatase-substrate network, and the protein domain co-occurrence network. All of these are available to query for and visualize existing phosphorylation events. Although P3DB only hosts experimentally identified phosphorylation data, it provides a plant phosphorylation prediction model for any unknown queries on the fly. P3DB is an entry point to the plant phosphorylation community to deposit and visualize any customized data sets within this systems biology framework. Nowadays, P3DB has become one of the major bioinformatics platforms of protein phosphorylation in plant biology.

PMID: 28150236 [PubMed - in process]

Commentary: Systems Biology Approach to Model the Life Cycle of Trypanosoma cruzi.

Front Cell Infect Microbiol. 2017;7:1

Authors: Carrea A, Diambra L

PMID: 28149830 [PubMed - in process]