15,545 research outputs found

    Design and Implementation of Network Transfer Protocol for Big Genomic Data

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    Genomic data is growing exponentially due to next generation sequencing technologies (NGS) and their ability to produce massive amounts of data in a short time. NGS technologies generate big genomic data that needs to be exchanged between different locations efficiently and reliably. The current network transfer protocols rely on Transmission Control Protocol (TCP) or User Datagram Protocol (UDP) protocols, ignoring data size and type. Universal application layer protocols such as HTTP are designed for wide variety of data types and are not particularly efficient for genomic data. Therefore, we present a new data-aware transfer protocol for genomic-data that increases network throughput and reduces latency, called Genomic Text Transfer Protocol (GTTP). In this paper, we design and implement a new network transfer protocol for big genomic DNA dataset that relies on the Hypertext Transfer Protocol (HTTP). Modification to content-encoding of HTTP has been done that would transfer big genomic DNA datasets using machine-to-machine (M2M) and client(s)-server topologies. Our results show that our modification to HTTP reduces the transmitted data by 75% of original data and still be able to regenerate the data at the client side for bioinformatics analysis. Consequently, the transfer of data using GTTP is shown to be much faster (about 8 times faster than HTTP) when compared with regular HTTP

    Review on DNA Cryptography

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    Cryptography is the science that secures data and communication over the network by applying mathematics and logic to design strong encryption methods. In the modern era of e-business and e-commerce the protection of confidentiality, integrity and availability (CIA triad) of stored information as well as of transmitted data is very crucial. DNA molecules, having the capacity to store, process and transmit information, inspires the idea of DNA cryptography. This combination of the chemical characteristics of biological DNA sequences and classical cryptography ensures the non-vulnerable transmission of data. In this paper we have reviewed the present state of art of DNA cryptography.Comment: 31 pages, 12 figures, 6 table

    Comparative Genomics of Cyanobacterial Symbionts Reveals Distinct, Specialized Metabolism in Tropical Dysideidae Sponges.

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    Marine sponges are recognized as valuable sources of bioactive metabolites and renowned as petri dishes of the sea, providing specialized niches for many symbiotic microorganisms. Sponges of the family Dysideidae are well documented to be chemically talented, often containing high levels of polyhalogenated compounds, terpenoids, peptides, and other classes of bioactive small molecules. This group of tropical sponges hosts a high abundance of an uncultured filamentous cyanobacterium, Hormoscilla spongeliae Here, we report the comparative genomic analyses of two phylogenetically distinct Hormoscilla populations, which reveal shared deficiencies in essential pathways, hinting at possible reasons for their uncultivable status, as well as differing biosynthetic machinery for the production of specialized metabolites. One symbiont population contains clustered genes for expanded polybrominated diphenylether (PBDE) biosynthesis, while the other instead harbors a unique gene cluster for the biosynthesis of the dysinosin nonribosomal peptides. The hybrid sequencing and assembly approach utilized here allows, for the first time, a comprehensive look into the genomes of these elusive sponge symbionts.IMPORTANCE Natural products provide the inspiration for most clinical drugs. With the rise in antibiotic resistance, it is imperative to discover new sources of chemical diversity. Bacteria living in symbiosis with marine invertebrates have emerged as an untapped source of natural chemistry. While symbiotic bacteria are often recalcitrant to growth in the lab, advances in metagenomic sequencing and assembly now make it possible to access their genetic blueprint. A cell enrichment procedure, combined with a hybrid sequencing and assembly approach, enabled detailed genomic analysis of uncultivated cyanobacterial symbiont populations in two chemically rich tropical marine sponges. These population genomes reveal a wealth of secondary metabolism potential as well as possible reasons for historical difficulties in their cultivation

    Efficient, Dependable Storage of Human Genome Sequencing Data

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    A compreensão do genoma humano impacta várias áreas da vida. Os dados oriundos do genoma humano são enormes pois existem milhões de amostras a espera de serem sequenciadas e cada genoma humano sequenciado pode ocupar centenas de gigabytes de espaço de armazenamento. Os genomas humanos são críticos porque são extremamente valiosos para a investigação e porque podem fornecer informações delicadas sobre o estado de saúde dos indivíduos, identificar os seus dadores ou até mesmo revelar informações sobre os parentes destes. O tamanho e a criticidade destes genomas, para além da quantidade de dados produzidos por instituições médicas e de ciências da vida, exigem que os sistemas informáticos sejam escaláveis, ao mesmo tempo que sejam seguros, confiáveis, auditáveis e com custos acessíveis. As infraestruturas de armazenamento existentes são tão caras que não nos permitem ignorar a eficiência de custos no armazenamento de genomas humanos, assim como em geral estas não possuem o conhecimento e os mecanismos adequados para proteger a privacidade dos dadores de amostras biológicas. Esta tese propõe um sistema de armazenamento de genomas humanos eficiente, seguro e auditável para instituições médicas e de ciências da vida. Ele aprimora os ecossistemas de armazenamento tradicionais com técnicas de privacidade, redução do tamanho dos dados e auditabilidade a fim de permitir o uso eficiente e confiável de infraestruturas públicas de computação em nuvem para armazenar genomas humanos. As contribuições desta tese incluem (1) um estudo sobre a sensibilidade à privacidade dos genomas humanos; (2) um método para detetar sistematicamente as porções dos genomas que são sensíveis à privacidade; (3) algoritmos de redução do tamanho de dados, especializados para dados de genomas sequenciados; (4) um esquema de auditoria independente para armazenamento disperso e seguro de dados; e (5) um fluxo de armazenamento completo que obtém garantias razoáveis de proteção, segurança e confiabilidade a custos modestos (por exemplo, menos de 1/Genoma/Ano),integrandoosmecanismospropostosaconfigurac\co~esdearmazenamentoapropriadasTheunderstandingofhumangenomeimpactsseveralareasofhumanlife.Datafromhumangenomesismassivebecausetherearemillionsofsamplestobesequenced,andeachsequencedhumangenomemaysizehundredsofgigabytes.Humangenomesarecriticalbecausetheyareextremelyvaluabletoresearchandmayprovidehintsonindividualshealthstatus,identifytheirdonors,orrevealinformationaboutdonorsrelatives.Theirsizeandcriticality,plustheamountofdatabeingproducedbymedicalandlifesciencesinstitutions,requiresystemstoscalewhilebeingsecure,dependable,auditable,andaffordable.Currentstorageinfrastructuresaretooexpensivetoignorecostefficiencyinstoringhumangenomes,andtheylacktheproperknowledgeandmechanismstoprotecttheprivacyofsampledonors.Thisthesisproposesanefficientstoragesystemforhumangenomesthatmedicalandlifesciencesinstitutionsmaytrustandafford.Itenhancestraditionalstorageecosystemswithprivacyaware,datareduction,andauditabilitytechniquestoenabletheefficient,dependableuseofmultitenantinfrastructurestostorehumangenomes.Contributionsfromthisthesisinclude(1)astudyontheprivacysensitivityofhumangenomes;(2)todetectgenomesprivacysensitiveportionssystematically;(3)specialiseddatareductionalgorithmsforsequencingdata;(4)anindependentauditabilityschemeforsecuredispersedstorage;and(5)acompletestoragepipelinethatobtainsreasonableprivacyprotection,security,anddependabilityguaranteesatmodestcosts(e.g.,lessthan1/Genoma/Ano), integrando os mecanismos propostos a configurações de armazenamento apropriadasThe understanding of human genome impacts several areas of human life. Data from human genomes is massive because there are millions of samples to be sequenced, and each sequenced human genome may size hundreds of gigabytes. Human genomes are critical because they are extremely valuable to research and may provide hints on individuals’ health status, identify their donors, or reveal information about donors’ relatives. Their size and criticality, plus the amount of data being produced by medical and life-sciences institutions, require systems to scale while being secure, dependable, auditable, and affordable. Current storage infrastructures are too expensive to ignore cost efficiency in storing human genomes, and they lack the proper knowledge and mechanisms to protect the privacy of sample donors. This thesis proposes an efficient storage system for human genomes that medical and lifesciences institutions may trust and afford. It enhances traditional storage ecosystems with privacy-aware, data-reduction, and auditability techniques to enable the efficient, dependable use of multi-tenant infrastructures to store human genomes. Contributions from this thesis include (1) a study on the privacy-sensitivity of human genomes; (2) to detect genomes’ privacy-sensitive portions systematically; (3) specialised data reduction algorithms for sequencing data; (4) an independent auditability scheme for secure dispersed storage; and (5) a complete storage pipeline that obtains reasonable privacy protection, security, and dependability guarantees at modest costs (e.g., less than 1/Genome/Year) by integrating the proposed mechanisms with appropriate storage configurations

    EsPRESSo: Efficient Privacy-Preserving Evaluation of Sample Set Similarity

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    Electronic information is increasingly often shared among entities without complete mutual trust. To address related security and privacy issues, a few cryptographic techniques have emerged that support privacy-preserving information sharing and retrieval. One interesting open problem in this context involves two parties that need to assess the similarity of their datasets, but are reluctant to disclose their actual content. This paper presents an efficient and provably-secure construction supporting the privacy-preserving evaluation of sample set similarity, where similarity is measured as the Jaccard index. We present two protocols: the first securely computes the (Jaccard) similarity of two sets, and the second approximates it, using MinHash techniques, with lower complexities. We show that our novel protocols are attractive in many compelling applications, including document/multimedia similarity, biometric authentication, and genetic tests. In the process, we demonstrate that our constructions are appreciably more efficient than prior work.Comment: A preliminary version of this paper was published in the Proceedings of the 7th ESORICS International Workshop on Digital Privacy Management (DPM 2012). This is the full version, appearing in the Journal of Computer Securit

    Balancing Selection at the Tomato RCR3 Guardee Gene Family Maintains Variation in Strength of Pathogen Defense

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    Coevolution between hosts and pathogens is thought to occur between interacting molecules of both species. This results in the maintenance of genetic diversity at pathogen antigens (or so-called effectors) and host resistance genes such as the major histocompatibility complex (MHC) in mammals or resistance (R) genes in plants. In plant-pathogen interactions, the current paradigm posits that a specific defense response is activated upon recognition of pathogen effectors via interaction with their corresponding R proteins. According to the''Guard-Hypothesis,'' R proteins (the ``guards'') can sense modification of target molecules in the host (the ``guardees'') by pathogen effectors and subsequently trigger the defense response. Multiple studies have reported high genetic diversity at R genes maintained by balancing selection. In contrast, little is known about the evolutionary mechanisms shaping the guardee, which may be subject to contrasting evolutionary forces. Here we show that the evolution of the guardee RCR3 is characterized by gene duplication, frequent gene conversion, and balancing selection in the wild tomato species Solanum peruvianum. Investigating the functional characteristics of 54 natural variants through in vitro and in planta assays, we detected differences in recognition of the pathogen effector through interaction with the guardee, as well as substantial variation in the strength of the defense response. This variation is maintained by balancing selection at each copy of the RCR3 gene. Our analyses pinpoint three amino acid polymorphisms with key functional consequences for the coevolution between the guardee (RCR3) and its guard (Cf-2). We conclude that, in addition to coevolution at the ``guardee-effector'' interface for pathogen recognition, natural selection acts on the ``guard-guardee'' interface. Guardee evolution may be governed by a counterbalance between improved activation in the presence and prevention of auto-immune responses in the absence of the corresponding pathogen

    Whole genome sequencing and microsatellite analysis of the Plasmodium falciparum E5 NF54 strain show that the var, rifin and stevor gene families follow Mendelian inheritance

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    Background: Plasmodium falciparum exhibits a high degree of inter-isolate genetic diversity in its variant surface antigen (VSA) families: P. falciparum erythrocyte membrane protein 1, repetitive interspersed family (RIFIN) and subtelomeric variable open reading frame (STEVOR). The role of recombination for the generation of this diversity is a subject of ongoing research. Here the genome of E5, a sibling of the 3D7 genome strain is presented. Short and long read whole genome sequencing (WGS) techniques (Ilumina, Pacific Bioscience) and a set of 84 microsatellites (MS) were employed to characterize the 3D7 and non-3D7 parts of the E5 genome. This is the first time that VSA genes in sibling parasites were analysed with long read sequencing technology. Results: Of the 5733 E5 genes only 278 genes, mostly var and rifin/stevor genes, had no orthologues in the 3D7 genome. WGS and MS analysis revealed that chromosomal crossovers occurred at a rate of 0–3 per chromosome. var, stevor and rifin genes were inherited within the respective non-3D7 or 3D7 chromosomal context. 54 of the 84 MS PCR fragments correctly identified the respective MS as 3D7- or non-3D7 and this correlated with var and rifin/stevor gene inheritance in the adjacent chromosomal regions. E5 had 61 var and 189 rifin/stevor genes. One large non-chromosomal recombination event resulted in a new var gene on chromosome 14. The remainder of the E5 3D7-type subtelomeric and central regions were identical to 3D7. Conclusions: The data show that the rifin/stevor and var gene families represent the most diverse compartments of the P. falciparum genome but that the majority of var genes are inherited without alterations within their respective parental chromosomal context. Furthermore, MS genotyping with 54 MS can successfully distinguish between two sibling progeny of a natural P. falciparum cross and thus can be used to investigate identity by descent in field isolates

    I2ECR: Integrated and Intelligent Environment for Clinical Research

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    Clinical trials are designed to produce new knowledge about a certain disease, drug or treatment. During these studies, a huge amount of data is collected about participants, therapies, clinical procedures, outcomes, adverse events and so on. A multicenter, randomized, phase III clinical trial in Hematology enrolls up to hundreds of subjects and evaluates post-treatment outcomes on stratified sub- groups of subjects for a period of many years. Therefore, data collection in clinical trials is becoming complex, with huge amount of clinical and biological variables. Outside the medical field, data warehouses (DWs) are widely employed. A Data Ware-house is a “collection of integrated, subject-oriented databases designed to support the decision-making process”. To verify whether DWs might be useful for data quality and association analysis, a team of biomedical engineers, clinicians, biologists and statisticians developed the “I2ECR” project. I2ECR is an Integrated and Intelligent Environment for Clinical Research where clinical and omics data stand together for clinical use (reporting) and for generation of new clinical knowledge. I2ECR has been built from the “MCL0208” phase III, prospective, clinical trial, sponsored by the Fondazione Italiana Linfomi (FIL); this is actually a translational study, accounting for many clinical data, along with several clinical prognostic indexes (e.g. MIPI - Mantle International Prognostic Index), pathological information, treatment and outcome data, biological assessments of disease (MRD - Minimal Residue Disease), as well as many biological, ancillary studies, such as Mutational Analysis, Gene Expression Profiling (GEP) and Pharmacogenomics. In this trial forty-eight Italian medical centers were actively involved, for a total of 300 enrolled subjects. Therefore, I2ECR main objectives are: • to propose an integration project on clinical and molecular data quality concepts. The application of a clear row-data analysis as well as clinical trial monitoring strategies to implement a digital platform where clinical, biological and “omics” data are imported from different sources and well-integrated in a data- ware-house • to be a dynamic repository of data congruency quality rules. I2ECR allows to monitor, in a semi-automatic manner, the quality of data, in relation to the clinical data imported from eCRFs (electronic Case Report Forms) and from biologic and mutational datasets internally edited by local laboratories. Therefore, I2ECR will be able to detect missing data and mistakes derived from non-conventional data- entry activities by centers. • to provide to clinical stake-holders a platform from where they can easily design statistical and data mining analysis. The term Data Mining (DM) identifies a set of tools to searching for hidden patterns of interest in large and multivariate datasets. The applications of DM techniques in the medical field range from outcome prediction and patient classification to genomic medicine and molecular biology. I2ECR allows to clinical stake-holders to propose innovative methods of supervised and unsupervised feature extraction, data classification and statistical analysis on heterogeneous datasets associated to the MCL0208 clinical trial. Although MCL0208 study is the first example of data-population of I2ECR, the environment will be able to import data from clinical studies designed for other onco-hematologic diseases, too

    Big Defensins, a Diverse Family of Antimicrobial Peptides That Follows Different Patterns of Expression in Hemocytes of the Oyster Crassostrea gigas

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    Background: Big defensin is an antimicrobial peptide composed of a highly hydrophobic N-terminal region and a cationic C-terminal region containing six cysteine residues involved in three internal disulfide bridges. While big defensin sequences have been reported in various mollusk species, few studies have been devoted to their sequence diversity, gene organization and their expression in response to microbial infections. Findings: Using the high-throughput Digital Gene Expression approach, we have identified in Crassostrea gigas oysters several sequences coding for big defensins induced in response to a Vibrio infection. We showed that the oyster big defensin family is composed of three members (named Cg-BigDef1, Cg-BigDef2 and Cg-BigDef3) that are encoded by distinct genomic sequences. All Cg-BigDefs contain a hydrophobic N-terminal domain and a cationic C-terminal domain that resembles vertebrate beta-defensins. Both domains are encoded by separate exons. We found that big defensins form a group predominantly present in mollusks and closer to vertebrate defensins than to invertebrate and fungi CS alpha beta-containing defensins. Moreover, we showed that Cg-BigDefs are expressed in oyster hemocytes only and follow different patterns of gene expression. While Cg-BigDef3 is non-regulated, both Cg-BigDef1 and Cg-BigDef2 transcripts are strongly induced in response to bacterial challenge. Induction was dependent on pathogen associated molecular patterns but not damage-dependent. The inducibility of Cg-BigDef1 was confirmed by HPLC and mass spectrometry, since ions with a molecular mass compatible with mature Cg-BigDef1 (10.7 kDa) were present in immune-challenged oysters only. From our biochemical data, native Cg-BigDef1 would result from the elimination of a prepropeptide sequence and the cyclization of the resulting N-terminal glutamine residue into a pyroglutamic acid. Conclusions: We provide here the first report showing that big defensins form a family of antimicrobial peptides diverse not only in terms of sequences but also in terms of genomic organization and regulation of gene expression
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