Is congenital pulmonary airway malformation really a rare disease? Result of a prospective registry with universal antenatal screening program.

Pediatr Surg Int. 2016 Oct 21;

Authors: Lau CT, Kan A, Shek N, Tam P, Wong KK

Abstract
BACKGROUND: Congenital pulmonary airway malformation (CPAM) is an increasingly recognized disease with potential mortality. Owing to limited published studies, the true incidence is yet to be determined. We carried out this prospective study with the aim to estimate its true incidence on a population basis.
METHODS: An antenatal ultrasonography program was implemented since 2009. Fetuses with suspected intra-thoracic lesions were monitored by regular follow-ups. Antenatal course, postnatal outcomes, and other demographics were compared to those of patients with CPAM in the previous decades (1989-2008). The incidence of CPAM was calculated in different periods.
RESULTS: 66 CPAM patients were identified between 2009 and 2014 with 62 patients being detected by antenatal scan. In contrast, 45 patients were identified between 1989 and 2008 with 27 patients being detected antenatally. The incidence rate during the past and recent period was estimated as ~1 in 27,400 and ~1 in 7200 live births, respectively (p = 0.024).
CONCLUSION: With increasing awareness of clinicians and the universal use of latest ultrasound technology, it is likely that more CPAM cases will be detected in the future. Here, we presented our best estimated incidence rate of CPAM, yet only a larger scale study can reveal its true incidence.

PMID: 27770196 [PubMed - as supplied by publisher]

Structural and functional analogies and differences between histidine decarboxylase and aromatic L-amino acid decarboxylase molecular networks: Biomedical implications.

Pharmacol Res. 2016 Oct 18;:

Authors: Sanchez-Jiménez F, Pino-Ángeles A, Rodríguez-López R, Morales M, Urdiales JL

Abstract
Human histidine decarboxylase (HDC) and dopa decarboxilase (DDC) are highly homologous enzymes responsible for the synthesis of biogenic amines (BA) like histamine, and serotonin and dopamine, respectively. The enzymes share many structural and functional analogies, while their product metabolisms also follow similar patterns that are confluent in some metabolic steps. They are involved in common physiological functions, such as neurotransmission, gastrointestinal track function, immunity, cell growth and cell differentiation. As a consequence, metabolic elements of both BA subfamilies are also co-participants in a long list of human diseases. This review summarizes the analogies and differences in their origin (HDC and DDC) as well as their common pathophysiological scenarios. The major gaps of information are also underlined, as they delay the possibility of holistic approaches that would help personalized medicine and pharmacological iniciatives for prevalent and rare diseases.

PMID: 27769832 [PubMed - as supplied by publisher]

Brain metabolite alterations in infants born preterm with intrauterine growth restriction: association with structural changes and neurodevelopmental outcome.

Am J Obstet Gynecol. 2016 Sep 22;:

Authors: Simões RV, Muñoz-Moreno E, Cruz-Lemini M, Eixarch E, Bargalló N, Sanz-Cortes M, Gratacós E

Abstract
BACKGROUND: Intrauterine growth restriction and premature birth represent 2 independent problems that may occur simultaneously and contribute to impaired neurodevelopment.
OBJECTIVE: The objective of the study was to assess changes in the frontal lobe metabolic profiles of 1 year old intrauterine growth restriction infants born prematurely and adequate-for-gestational-age controls, both premature and term adequate for gestational age and their association with brain structural and biophysical parameters and neurodevelopmental outcome at 2 years.
STUDY DESIGN: A total of 26 prematurely born intrauterine growth restriction infants (birthweight <10th centile for gestational age), 22 prematurely born but adequate for gestational age controls, and 26 term adequate-for-gestational-age infants underwent brain magnetic resonance imaging and magnetic resonance spectroscopy at 1 year of age during natural sleep, on a 3 Tesla scanner. All brain T1-weighted and diffusion-weighted images were acquired along with short echo time single-voxel proton spectra from the frontal lobe. Magnetic resonance imaging/magnetic resonance spectroscopy data were processed to derive structural, biophysical, and metabolic information, respectively. Neurodevelopment was evaluated at 2 years of age using the Bayley Scales 3rd edition, assessing cognitive, language, motor, socioemotional, and adaptive behavior.
RESULTS: Prematurely born intrauterine growth restriction infants had slightly smaller brain volumes and increased frontal lobe white matter mean diffusivity compared with both prematurely born but adequate for gestational age and term adequate for gestational age controls. Frontal lobe N-acetylaspartate levels were significantly lower in prematurely born intrauterine growth restriction than in prematurely born but adequate for gestational age infants but increased in prematurely born but adequate for gestational age compared with term adequate-for-gestational-age infants. The prematurely born intrauterine growth restriction group also showed slightly lower choline compounds, borderline decrements of estimated glutathione levels, and increased myoinositol to choline ratios, compared with prematurely born but adequate for gestational age controls. These specific metabolite changes were locally correlated to lower gray matter content and increased mean diffusivity and reduced white matter fraction and fractional anisotropy. Prematurely born intrauterine growth restriction infants also showed a tendency for poorer neurodevelopmental outcome at 2 years, associated with lower levels of frontal lobe N-acetylaspartate at 1 year within the preterm subset.
CONCLUSIONS: Preterm intrauterine growth restriction infants showed altered brain metabolite profiles during a critical stage of brain maturation, which correlate with brain structural and biophysical parameters and neurodevelopmental outcome. Our results suggest altered neurodevelopmental trajectories in preterm intrauterine growth restriction and adequate-for-gestational-age infants, compared with term adequate-for-gestational-age infants, which require further characterization.

PMID: 27667762 [PubMed - as supplied by publisher]

[Erdheim-Chester disease, an incredible simulator. Cases reports and review of literature].

Neurocirugia (Astur). 2016 Nov - Dec;27(6):296-303

Authors: Rascón-Ramírez FJ, Avecillas-Chasín JM, Rodríguez-Boto G, Subhi-Issa I, Salazar A OA, Sallabanda D K

Abstract
Erdheim-Chester disease is a non-Langerhans histiocytosis. Until 2014 at least 550 cases have been reported. According to European Rare Disease Organization and National Organization for Rare Disorders it is a rare disease. The most common symptom is bone pain in the lower extremities and it usually appears between the 5th and 7th decades of life. The diagnostic is based on immunohistochemical results: S100(+/-), CD68(+), and CD1a(-), the latter 2 are mandatory. The best treatment nowadays is alpha-interferon or pegylated alpha-2. The overall survival is 96% at one year and 68% at 5 years. Central nervous system involvement is associated with a worse outcome. Two cases are presentedwith central nervous system lesions in the absence of lesions in other organs on their onset. Very few cases have been reported with this kind of presentation. We also noted that these patients had recurrences or new lesions at 8 months. A follow-up is proposed with brain MRI and thoraco-abdominal PET every 3-4 months.

PMID: 27091228 [PubMed - in process]

A computational interactome and functional annotation for the human proteome.

Elife. 2016 Oct 22;5:

Authors: Garzón JI, Deng L, Murray D, Shapira S, Petrey D, Honig B

Abstract
We present a database, PrePPI (Predicting Protein-Protein Interactions), of more than 1.35 million predicted protein-protein interactions (PPIs). Of these at least 127,000 are expected to constitute direct physical interactions although the actual number may be much larger (~500,000). The current PrePPI, which contains predicted interactions for about 85% of the human proteome is related to an earlier version but is based on additional sources of interaction evidence and is far larger in scope. The use of structural relationships allows PrePPI to infer numerous previously unreported interactions. PrePPI has been subjected to a series of validation tests including reproducing known interactions, recapitulating multi-protein complexes, analysis of disease associated SNPs, and identifying functional relationships between interacting proteins. We show, using Gene Set Enrichment Analysis (GSEA), that predicted interaction partners can be used to annotate a protein's function. We provide annotations for most human proteins, including many annotated as having unknown function.

PMID: 27770567 [PubMed - as supplied by publisher]

Effect of amino acid supplementation on titer and glycosylation distribution in hybridoma cell cultures-Systems biology-based interpretation using genome-scale metabolic flux balance model and multivariate data analysis.

Biotechnol Prog. 2016 Sep;32(5):1163-1173

Authors: Reimonn TM, Park SY, Agarabi CD, Brorson KA, Yoon S

Abstract
Genome-scale flux balance analysis (FBA) is a powerful systems biology tool to characterize intracellular reaction fluxes during cell cultures. FBA estimates intracellular reaction rates by optimizing an objective function, subject to the constraints of a metabolic model and media uptake/excretion rates. A dynamic extension to FBA, dynamic flux balance analysis (DFBA), can calculate intracellular reaction fluxes as they change during cell cultures. In a previous study by Read et al. (2013), a series of informed amino acid supplementation experiments were performed on twelve parallel murine hybridoma cell cultures, and this data was leveraged for further analysis (Read et al., Biotechnol Prog. 2013;29:745-753). In order to understand the effects of media changes on the model murine hybridoma cell line, a systems biology approach is applied in the current study. Dynamic flux balance analysis was performed using a genome-scale mouse metabolic model, and multivariate data analysis was used for interpretation. The calculated reaction fluxes were examined using partial least squares and partial least squares discriminant analysis. The results indicate media supplementation increases product yield because it raises nutrient levels extending the growth phase, and the increased cell density allows for greater culture performance. At the same time, the directed supplementation does not change the overall metabolism of the cells. This supports the conclusion that product quality, as measured by glycoform assays, remains unchanged because the metabolism remains in a similar state. Additionally, the DFBA shows that metabolic state varies more at the beginning of the culture but less by the middle of the growth phase, possibly due to stress on the cells during inoculation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1163-1173, 2016.

PMID: 27452371 [PubMed - in process]

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Prioritization, clustering and functional annotation of MicroRNAs using latent semantic indexing of MEDLINE abstracts.

BMC Bioinformatics. 2016 Oct 6;17(Suppl 13):350

Authors: Roy S, Curry BC, Madahian B, Homayouni R

Abstract
BACKGROUND: The amount of scientific information about MicroRNAs (miRNAs) is growing exponentially, making it difficult for researchers to interpret experimental results. In this study, we present an automated text mining approach using Latent Semantic Indexing (LSI) for prioritization, clustering and functional annotation of miRNAs.
RESULTS: For approximately 900 human miRNAs indexed in miRBase, text documents were created by concatenating titles and abstracts of MEDLINE citations which refer to the miRNAs. The documents were parsed and a weighted term-by-miRNA frequency matrix was created, which was subsequently factorized via singular value decomposition to extract pair-wise cosine values between the term (keyword) and miRNA vectors in reduced rank semantic space. LSI enables derivation of both explicit and implicit associations between entities based on word usage patterns. Using miR2Disease as a gold standard, we found that LSI identified keyword-to-miRNA relationships with high accuracy. In addition, we demonstrate that pair-wise associations between miRNAs can be used to group them into categories which are functionally aligned. Finally, term ranking by querying the LSI space with a group of miRNAs enabled annotation of the clusters with functionally related terms.
CONCLUSIONS: LSI modeling of MEDLINE abstracts provides a robust and automated method for miRNA related knowledge discovery. The latest collection of miRNA abstracts and LSI model can be accessed through the web tool miRNA Literature Network (miRLiN) at http://bioinfo.memphis.edu/mirlin .

PMID: 27766940 [PubMed - in process]

Data Integration and Mining for Synthetic Biology Design.

ACS Synth Biol. 2016 Oct 21;5(10):1086-1097

Authors: Mısırlı G, Hallinan J, Pocock M, Lord P, McLaughlin JA, Sauro H, Wipat A

Abstract
One aim of synthetic biologists is to create novel and predictable biological systems from simpler modular parts. This approach is currently hampered by a lack of well-defined and characterized parts and devices. However, there is a wealth of existing biological information, which can be used to identify and characterize biological parts, and their design constraints in the literature and numerous biological databases. However, this information is spread among these databases in many different formats. New computational approaches are required to make this information available in an integrated format that is more amenable to data mining. A tried and tested approach to this problem is to map disparate data sources into a single data set, with common syntax and semantics, to produce a data warehouse or knowledge base. Ontologies have been used extensively in the life sciences, providing this common syntax and semantics as a model for a given biological domain, in a fashion that is amenable to computational analysis and reasoning. Here, we present an ontology for applications in synthetic biology design, SyBiOnt, which facilitates the modeling of information about biological parts and their relationships. SyBiOnt was used to create the SyBiOntKB knowledge base, incorporating and building upon existing life sciences ontologies and standards. The reasoning capabilities of ontologies were then applied to automate the mining of biological parts from this knowledge base. We propose that this approach will be useful to speed up synthetic biology design and ultimately help facilitate the automation of the biological engineering life cycle.

PMID: 27110921 [PubMed - in process]

Economic analysis of pharmacogenomic-guided clopidogrel treatment in Serbian patients with myocardial infarction undergoing primary percutaneous coronary intervention.

Pharmacogenomics. 2016 Oct 21;

Authors: Mitropoulou C, Fragoulakis V, Rakicevic LB, Novkovic MM, Vozikis A, Matic DM, Antonijevic NM, Radojkovic DP, van Schaik RH, Patrinos GP

Abstract
INTRODUCTION: Clopidogrel, which is activated by the CYP2C19 enzyme, is among the drugs for which all major regulatory agencies recommend genetic testing to be performed to identify a patient's CYP2C19 genotype in order to determine the optimal antiplatelet therapeutic scheme. The CYP2C19*2 and CYP2C19*3 variants are loss-of-function alleles, leading to abolished CYP2C19 function and thus have the risk of thrombotic events for carriers of these alleles on standard dosages, while the CYP2C19*17 allele results in CYP2C19 hyperactivity.
AIMS: Here, we report our findings from a retrospective study to assess whether genotyping for the CYP2C19*2 allele was cost effective for myocardial infarction patients receiving clopidogrel treatment in the Serbian population compared with the nongenotype-guided treatment.
RESULTS: We found that 59.3% of the CYP2C19*1/*1 patients had a minor or major bleeding event versus 42.85% of the CYP2C19*1/*2 and *2/*2, while a reinfarction event occurred only in 2.3% of the CYP21C9*1/*1 patients, compared with 11.2% of the CYP2C19*1/*2 and CYP2C19*2/*2 patients. There were subtle differences between the two patient groups, as far as the duration of hospitalization and rehabilitation is concerned, in favor of the CYP2C19*1/*1 group. The mean cost for the CYP2C19*1/*1 patients was estimated at €2547 versus €2799 in the CYP2C19*1/*2 and CYP2C19*2/*2 patients. Furthermore, based on the overall CYP2C19*1/*2 genotype frequencies in the Serbian population, a break-even point analysis indicated that performing the genetic test prior to drug prescription represents a cost-saving option, saving €13 per person on average.
CONCLUSION: Overall, our data demonstrate that pharmacogenomics-guided clopidogrel treatment may represent a cost-saving approach for the management of myocardial infarction patients undergoing primary percutaneous coronary intervention in Serbia.

PMID: 27767438 [PubMed - as supplied by publisher]

Addressing ethical challenges at the intersection of pharmacogenomics and primary care using deliberative consultations.

Pharmacogenomics. 2016 Oct 21;

Authors: Longo C, Rahimzadeh V, O'Doherty K, Bartlett G

Abstract
AIM: Primary care physicians will play a central role in the successful implementation of pharmacogenomics (PGx); however, important challenges remain. We explored the perspectives of stakeholders on key challenges of the PGx translation process in primary care using deliberative consultations.
METHODS: Primary care physicians, patients and policy-makers attended deliberations, where they discussed four ethical questions raised by PGx research and implementation in the primary care context.
RESULTS: Stakeholders voiced skepticism regarding PGx funding, commercialization, regulation, maintenance of an equal access healthcare system and restructuring of health research incentives and priorities in the public sector.
CONCLUSION: Deliberants developed governing principles for a PGx-specific charter of ethics, aiming to protect the interests of patients, and outlined recommendations for the future of PGx in primary care.

PMID: 27767407 [PubMed - as supplied by publisher]

Correlation of SIN3A genomic variants with β-hemoglobinopathies disease severity and hydroxyurea treatment efficacy.

Pharmacogenomics. 2016 Oct 21;

Authors: Gravia A, Chondrou V, Kolliopoulou A, Kourakli A, John A, Symeonidis A, Ali BR, Sgourou A, Papachatzopoulou A, Katsila T, Patrinos GP

Abstract
AIMS: Hemoglobinopathies, particularly β-thalassemia and sickle cell disease, are characterized by great phenotypic variability in terms of disease severity, while notable differences have been observed in hydroxyurea treatment efficacy. In both cases, the observed phenotypic diversity is mostly dependent on the elevated fetal hemoglobin levels, resulting from the persistent fetal globin gene expression in the adult erythroid stage orchestrated by intricate mechanisms that still remain only partly understood. We have previously shown that several protein factors act as modifiers of fetal hemoglobin production, exerting their effect via different pathways.
MATERIALS & METHODS: Here, we explored whether SIN3A could act as a modifier of fetal globin gene expression, as it interacts with KLF10, a known modifier of fetal hemoglobin production.
RESULTS: We show that SIN3A genomic variants are associated both with β-thalassemia disease severity (rs11072544) as well as hydroxyurea treatment response (rs7166737) in β-hemoglobinopathies patients.
CONCLUSION: Our findings further underline that fetal hemoglobin production is the result of a complex interplay in which several human globin gene cluster variants interact with protein factors encoded by modifier genes to produce the observed clinical outcome.

PMID: 27767389 [PubMed - as supplied by publisher]

The effect of SNPs in CYP450 in chloroquine/primaquine Plasmodium vivax malaria treatment.

Pharmacogenomics. 2016 Oct 21;

Authors: Sortica VA, Lindenau JD, Cunha MG, Ohnishi MD, Ventura AM, Ribeiro-Dos-Santos ÂK, Santos SE, Guimarães LS, Hutz MH

Abstract
BACKGROUND: Chloroquine/primaquine is the current therapy to eliminate Plasmodium vivax infection in the Amazon region.
AIMS: This study investigates CYP1A2, CYP2C8, CYP2C9, CYP3A4 and CYP3A5 genetic polymorphisms influence on cloroquine/primaquine treatment.
PATIENTS & METHODS: Generalized estimating equations analyses were performed to determine the genetic influence in parasitemia and/or gametocytemia clearance over treatment time in 164 patients.
RESULTS: An effect of CYP2C8 low-activity alleles on treatment was observed (p = 0.01). From baseline to first day of treatment, wild-type individuals achieved greater reduction of gametocytes than low-activity allele carriers. CYP2C9 and CYP3A5 genes showed a trend for gametocytemia and parasitemia clearance rates.
CONCLUSION: Future studies should be performed to access the extent of CYP2C8, CYP2C9 and CYP3A5 gene polymorphisms influence on cloroquine/primaquine treatment.

PMID: 27767381 [PubMed - as supplied by publisher]

Pharmacogenomics and histone deacetylase inhibitors.

Pharmacogenomics. 2016 Oct 21;

Authors: Goey AK, Sissung TM, Peer CJ, Figg WD

Abstract
The histone deacetylase inhibitor valproic acid (VPA) has been used for many decades in neurology and psychiatry. The more recent introduction of the histone deacetylase inhibitors (HDIs) belinostat, romidepsin and vorinostat for treatment of hematological malignancies indicates the increasing popularity of these agents. Belinostat, romidepsin and vorinostat are metabolized or transported by polymorphic enzymes or drug transporters. Thus, genotype-directed dosing could improve pharmacotherapy by reducing the risk of toxicities or preventing suboptimal treatment. This review provides an overview of clinical studies on the effects of polymorphisms on the pharmacokinetics, efficacy or toxicities of HDIs including belinostat, romidepsin, vorinostat, panobinostat, VPA and a number of novel compounds currently being tested in Phase I and II trials. Although pharmacogenomic studies for HDIs are scarce, available data indicate that therapy with belinostat (UGT1A1), romidepsin (ABCB1), vorinostat (UGT2B17) or VPA (UGT1A6) could be optimized by upfront genotyping.

PMID: 27767376 [PubMed - as supplied by publisher]

Human Environmental Disease Network: A computational model to assess toxicology of contaminants.

ALTEX. 2016 Oct 21;:

Authors: Taboureau O, Audouze K

Abstract
During the past decades, many epidemiological, toxicological and biological studies have been performed to assess the role of environmental chemicals as potential toxicants for diverse human disorders. However, the relationships between diseases based on chemical exposure have been rarely studied by computational biology. We developed a human environmental disease network (EDN) to explore and suggest novel disease-disease and chemical-disease relationships. The presented scored EDN model is built upon the integration on systems biology and chemical toxicology using chemical contaminants information and their disease relationships from the reported TDDB database. The resulting human EDN takes into consideration the level of evidence of the toxicant-disease relationships allowing including some degrees of significance in the disease-disease associations. Such network can be used to identify uncharacterized connections between diseases. Examples are discussed with type 2 diabetes (T2D). Additionally, this computational model allows to confirm already know chemical-disease links (e.g. bisphenol A and behavioral disorders) and also to reveal unexpected associations between chemicals and diseases (e.g. chlordane and olfactory alteration), thus predicting which chemicals may be risk factors to human health. With the proposed human EDN model, it is possible to explore common biological mechanism between two diseases through chemical exposure helping us to gain insight into disease etiology and comorbidity. Such computational approach is an alternative to animal testing supporting the 3R concept.

PMID: 27768803 [PubMed - as supplied by publisher]

Data for the qualitative modeling of the osmotic stress response to NaCl in Escherichia coli.

Data Brief. 2016 Dec;9:606-612

Authors: Ropers D, Métris A

Abstract
Qualitative modeling approaches allow to provide a coarse-grained description of the functioning of cellular networks when experimental data are scarce and heterogeneous. We translate the primary literature data on the response of Escherichia coli to hyperosmotic stress caused by NaCl addition into a piecewise linear (PL) model. We provide a data file of the qualitative model, which can be used for simulation of changes of protein concentrations and of DNA coiling during the physiological response of the bacterium to the stress. The qualitative model predictions are directly comparable to the available experimental data. This data is related to the research article entitled "Piecewise linear approximations to model the dynamics of adaptation to osmotic stress by food-borne pathogens" (Metris et al., 2016) [1].

PMID: 27766288 [PubMed - in process]

Attractor landscape analysis of colorectal tumorigenesis and its reversion.

BMC Syst Biol. 2016 Oct 20;10(1):96

Authors: Cho SH, Park SM, Lee HS, Lee HY, Cho KH

Abstract
BACKGROUND: Colorectal cancer arises from the accumulation of genetic mutations that induce dysfunction of intracellular signaling. However, the underlying mechanism of colorectal tumorigenesis driven by genetic mutations remains yet to be elucidated.
RESULTS: To investigate colorectal tumorigenesis at a system-level, we have reconstructed a large-scale Boolean network model of the human signaling network by integrating previous experimental results on canonical signaling pathways related to proliferation, metastasis, and apoptosis. Throughout an extensive simulation analysis of the attractor landscape of the signaling network model, we found that the attractor landscape changes its shape by expanding the basin of attractors for abnormal proliferation and metastasis along with the accumulation of driver mutations. A further hypothetical study shows that restoration of a normal phenotype might be possible by reversely controlling the attractor landscape. Interestingly, the targets of approved anti-cancer drugs were highly enriched in the identified molecular targets for the reverse control.
CONCLUSIONS: Our results show that the dynamical analysis of a signaling network based on attractor landscape is useful in acquiring a system-level understanding of tumorigenesis and developing a new therapeutic strategy.

PMID: 27765040 [PubMed - in process]

New Algorithm and Software (BNOmics) for Inferring and Visualizing Bayesian Networks from Heterogeneous Big Biological and Genetic Data.

J Comput Biol. 2016 Sep 28;

Authors: Gogoshin G, Boerwinkle E, Rodin AS

Abstract
Bayesian network (BN) reconstruction is a prototypical systems biology data analysis approach that has been successfully used to reverse engineer and model networks reflecting different layers of biological organization (ranging from genetic to epigenetic to cellular pathway to metabolomic). It is especially relevant in the context of modern (ongoing and prospective) studies that generate heterogeneous high-throughput omics datasets. However, there are both theoretical and practical obstacles to the seamless application of BN modeling to such big data, including computational inefficiency of optimal BN structure search algorithms, ambiguity in data discretization, mixing data types, imputation and validation, and, in general, limited scalability in both reconstruction and visualization of BNs. To overcome these and other obstacles, we present BNOmics, an improved algorithm and software toolkit for inferring and analyzing BNs from omics datasets. BNOmics aims at comprehensive systems biology-type data exploration, including both generating new biological hypothesis and testing and validating the existing ones. Novel aspects of the algorithm center around increasing scalability and applicability to varying data types (with different explicit and implicit distributional assumptions) within the same analysis framework. An output and visualization interface to widely available graph-rendering software is also included. Three diverse applications are detailed. BNOmics was originally developed in the context of genetic epidemiology data and is being continuously optimized to keep pace with the ever-increasing inflow of available large-scale omics datasets. As such, the software scalability and usability on the less than exotic computer hardware are a priority, as well as the applicability of the algorithm and software to the heterogeneous datasets containing many data types-single-nucleotide polymorphisms and other genetic/epigenetic/transcriptome variables, metabolite levels, epidemiological variables, endpoints, and phenotypes, etc.

PMID: 27681505 [PubMed - as supplied by publisher]

An Implementation-Focused Bio/Algorithmic Workflow for Synthetic Biology.

ACS Synth Biol. 2016 Oct 21;5(10):1127-1135

Authors: Goñi-Moreno A, Carcajona M, Kim J, Martínez-García E, Amos M, de Lorenzo V

Abstract
As synthetic biology moves away from trial and error and embraces more formal processes, workflows have emerged that cover the roadmap from conceptualization of a genetic device to its construction and measurement. This latter aspect (i.e., characterization and measurement of synthetic genetic constructs) has received relatively little attention to date, but it is crucial for their outcome. An end-to-end use case for engineering a simple synthetic device is presented, which is supported by information standards and computational methods and focuses on such characterization/measurement. This workflow captures the main stages of genetic device design and description and offers standardized tools for both population-based measurement and single-cell analysis. To this end, three separate aspects are addressed. First, the specific vector features are discussed. Although device/circuit design has been successfully automated, important structural information is usually overlooked, as in the case of plasmid vectors. The use of the Standard European Vector Architecture (SEVA) is advocated for selecting the optimal carrier of a design and its thorough description in order to unequivocally correlate digital definitions and molecular devices. A digital version of this plasmid format was developed with the Synthetic Biology Open Language (SBOL) along with a software tool that allows users to embed genetic parts in vector cargoes. This enables annotation of a mathematical model of the device's kinetic reactions formatted with the Systems Biology Markup Language (SBML). From that point onward, the experimental results and their in silico counterparts proceed alongside, with constant feedback to preserve consistency between them. A second aspect involves a framework for the calibration of fluorescence-based measurements. One of the most challenging endeavors in standardization, metrology, is tackled by reinterpreting the experimental output in light of simulation results, allowing us to turn arbitrary fluorescence units into relative measurements. Finally, integration of single-cell methods into a framework for multicellular simulation and measurement is addressed, allowing standardized inspection of the interplay between the carrier chassis and the culture conditions.

PMID: 27454551 [PubMed - in process]