Protein Secondary Structure Prediction using Parallelized Rule Induction from Coverings

Protein 3D structure prediction has always been an important research area in bioinformatics. In particular, the prediction of secondary structure has been a well-studied research topic. Despite the recent breakthrough of combining multiple sequence alignment information and artificial intelligence algorithms to predict protein secondary structure, the Q3 accuracy of various computational prediction algorithms rarely has exceeded 75%. In a previous paper [1], this research team presented a rule-based method called RT-RICO (Relaxed Threshold Rule Induction from Coverings) to predict protein secondary structure. The average Q3 accuracy on the sample datasets using RT-RICO was 80.3%, an improvement over comparable computational methods. Although this demonstrated that RT-RICO might be a promising approach for predicting secondary structure, the algorithm\u27s computational complexity and program running time limited its use. Herein a parallelized implementation of a slightly modified RT-RICO approach is presented. This new version of the algorithm facilitated the testing of a much larger dataset of 396 protein domains [2]. Parallelized RTRICO achieved a Q3 score of 74.6%, which is higher than the consensus prediction accuracy of 72.9% that was achieved for the same test dataset by a combination of four secondary structure prediction methods [2]

Protein secondary structure prediction using BLAST and relaxed threshold rule induction from coverings

Protein structure prediction has always been an important research area in bioinformatics and biochemistry. Despite the recent breakthrough of combining multiple sequence alignment information and artificial intelligence algorithms to predict protein secondary structure, the Q₃ accuracy of various computational prediction methods rarely has exceeded 75%; this status has changed little since 2003 when Rost stated that the currently best methods reach a level around 77% three-state per-residue accuracy. The application of artificial neural network methods to this problem is revolutionary in the sense that those techniques employ the homologues of proteins for training and prediction. In this dissertation, a different approach, RT-RICO (Relaxed Threshold Rule Induction from Coverings), is presented that instead uses association rule mining. This approach still makes use of the fundamental principle that structure is more conserved than sequence. However, rules between each known secondary structure element and its neighboring amino acid residues are established to perform the predictions. This dissertation consists of five research articles that discuss different prediction techniques and detailed rule-generation algorithms. The most recent prediction approach, BLAST-RT-RICO, achieved a Q₃ accuracy score of 89.93% on the standard test dataset RS126 and a Q₃ score of 87.71% on the standard test dataset CB396, an improvement over comparable computational methods. Herein one research article also discusses the results of examining those RT-RICO rules using an existing association rule visualization tool, modified to account for the non-Boolean characterization of protein secondary structure --Abstract, page iv

Protein Secondary Structure Prediction Using RT-RICO: A Rule-Based Approach

Protein structure prediction has always been an important research area in biochemistry. In particular, the prediction of protein secondary structure has been a well-studied research topic. The experimental methods currently used to determine protein structure are accurate, yet costly both in terms of equipment and time. Despite the recent breakthrough of combining multiple sequence alignment information and artificial intelligence algorithms to predict protein secondary structure, the Q3 accuracy of various computational prediction methods rarely has exceeded 75%. In this paper, a newly developed rule-based data-mining approach called RT-RICO (Relaxed Threshold Rule Induction from Coverings) is presented. This method identifies dependencies between amino acids in a protein sequence and generates rules that can be used to predict secondary structure. RT-RICO achieved a Q3 score of 81.75% on the standard test dataset RS 126 and a Q3 score of 79.19% on the standard test dataset CB396, an improvement over comparable computational methods

Characterization of PDF1 and its interaction with DELAY OF GERMINATION1 (DOG1) in the control of seed dormancy in Arabidopsis thaliana

Seed dormancy is defined as the incapacity of a viable seed to germinate under favourable conditions. It is established during seed maturation and reaches high levels in mature dry seeds. Dormancy is a complex adaptive trait that assures germination at proper time of the year at the onset of the favourable growing season. This trait is regulated by hormonal and environmental cues such as temperature and light. In Arabidopsis thaliana dormancy can be released by imbibing seeds at cold temperatures (stratification) or by storing seeds in dry conditions (after- ripening). The molecular mechanisms that regulate the induction and the release of dormancy are still poorly understood. Previous studies identified DELAY OF GERMINATION1 (DOG1) as a key regulator of seed dormancy in Arabidopsis. The dog1 mutant completely lacks seed dormancy and has no pleiotropic effects. DOG1 shows a seed-specific expression pattern and the abundance of its protein correlates with the dormancy level in freshly harvested seeds. However, this correlation is lacking in after-ripened seeds, suggesting that the protein activity is lost during after ripening (Nakabayashi et al., 2012). DOG1 encodes a protein with unknown function and unknown regulation. The phosphatase PDF1 was identified as an interactor of DOG1 in a yeast two hybrid assay. This thesis describes the relation between PDF1 and DOG1 which was investigated in order to gain further insights into the regulation of DOG1 and into the mechanisms controlling seed dormancy. A T-DNA insertion mutant named pdf1-1 showed increased dormancy. PDF1 and DOG1 were co-expressed during seed maturation, interacted in vivo and were shown to function in the same pathway independent from ABA. Two-dimensional gels analysis showed that DOG1 is targeted by two different post-translational modifications during after ripening and after imbibition. DOG1 shifted towards a lower pH during after-ripening, while imbibition caused a shift towards the basic side. In the pdf1-1 mutant DOG1 was detected at a lower pH in comparison to Columbia, indicating possible increased phosphorylation levels and implying a role of PDF1 in the dephosphorylation of DOG1. Moreover, the shift of DOG1 caused by the after-ripening was not observed in the pdf1-1 mutant, suggesting that the post-translational modifications of DOG1 are interdependent

Space benefits: The secondary application of aerospace technology in other sectors of the economy

Benefit cases of aerospace technology utilization are presented for manufacturing, transportation, utilities, and health. General, organization, geographic, and field center indexes are included

Systems of difference equations as a model for the Lorenz system

We consider systems of difference equations as a model for the Lorenz system of differential equations. Using the power series whose coefficients are the solutions of these systems, we define three real functions, that are approximation for the solutions of the Lorenz system

About Concrete Realization of Remote Metabolism

The idea of "remote metabolism" (or quantum credit card, as I have also called it) emerged more than a decade ago - and zero energy ontology (ZEO)provides the justication for it. The idea is that the system needing energy sends negative energy to a system able to receive the negative energy and make a transition to a lower energy state. This kind of mechanism would be ideal for biology, where rapid reactions to a changing environment are essential for survival. Originally this article was intended to summarize a more detailed model of remote metabolism, but the article expanded to a considerably more detailed view about TGD inspired biology than the earlier vision. It is shown that the basic notions of the theory of Ling about cell metabolism inspired by various anomalies have natural counterparts in TGD based model relying on the notion of magnetic body. Remote metabolism can be considered as a universal metabolic mechanism with magnetic body of ATP, or system containing it, carrying the metabolic energy required by the biological user. In particular, the role of ATP is discussed in Ling's theory and from the point of view of TGD-inspired theory of consciousness. It is easy to imagine new technologies relying on negative energy signals propagating to the geometric past and ZEO justifies these speculations. Remote metabolism could make possible a new kind of energy technology. The discoveries of Tesla made more than a century ago plus various free energy anomalies provide excellent material for developing these ideas, and one ends up with a concrete proposal for how dark photons and dark matter could be produced in capacitor-like systems analogous to cell membranes and acting as Josephson junctions andhow energy could be extracted from "large" magnetic bodies.The model identies Josephson frequency with the subharmonic of the frequency characterizing the periodicity of a periodic voltage perturbation assumed to correspond to cyclotron frequency in biological applications. Together with quantization conditions for charge and effective Planck constant it leads to precise quantitative predictions for capacitor-like systems acting as dark capacitors. Also a relationship between the magnetic field at the magnetic body of the system and the voltage of the capacitor-like Josephson junction emerges.The predictions allow new quantitative insights about biological evolution as emergence of Josephson junctions realized as capacitor-like systems both at thelevel of cell, DNA and proteins, and brain. heff can be related to Josephsonfrequency and cyclotron frequency and thus to measurable parameters. heffserves as a kind of intelligence quotient and its maximization requires the maximization of both the voltage and area of the membrane-like capacitor system involved. This is what has happened during evolution. Indeed, the internal cell membranes, cortical layers and DNA double strand in chromosomes are strongly folded, and the value of membrane electric field is roughly twice the value of the electric field for which dielectric breakdown occurs in air. Even 40 Hz thalamo-cortical resonance frequency can be understood in the framework of the model. The claimed properties of Tesla's "cold electricity" strongly suggest interpretation in terms of dark matter in TGD sense. This leads to a proposal that a transition to dark phase occurs when the value of voltage equals the rest mass of charged particle involved. This criterion generalizes to the case of cell membrane and relates the values of heff , p-adic prime p, and threshold potential for various charged particles to each other. The idea that nerve pulse corresponds to the breakdown of super-conductivity as a transition from dark to ordinary phase receives additional support. The resulting picture conforms surprisingly well with the earlier speculations involving dark matter and p-adically scaled variants of weak and color interactions in biologically relevant length scales. An extremely simple mechanism producing ATP involving only the kicking of two protonic Cooper pairs through the cell membrane by Josephson photon as a basic step isproposed. Also the proposal that neutrino Cooper pairs could be highly relevant not only for cognition and but also metabolism finds support

Evolutionäre Diversität der CLCA Gene zwischen Vögeln und Säugetieren

The chloride channel regulators, calcium activated (CLCA) gene family has mainly been associated with cancer and chronic inflammatory airway diseases but the presumably complex cellular functions of these gene products are still widely unknown. The family comprises four distinct genetic clusters in mammals, termed CLCA1 to CLCA4. It is highly complex and diverse and includes amplified or inactivated genes with a high degree of variation between species. For example, in contrast to mice with eight CLCAs including one inactivated gene, humans have only three intact CLCAs and one inactivated gene. The tissue and cellular expression patterns of different CLCA homologues within a species are also often redundant. This complexity and redundancy of the CLCA members might be a reason, why the function of this gene family has not been revealed yet based on a mammalian model organism. The complexity and redundancy of mammalian CLCAs raise two questions: Are the complexity and diversity of these genes unique features of mammals? And second, what is the evolutionary background of these peculiar developments? To address these questions, data on CLCA homologues obtained from evolutionarily more distant species are needed. Recently, a rather simple CLCA gene locus was predicted for the chicken, comprising only two CLCA genes. In a phylogenetic analysis, the first galline CLCA gene product, gCLCA1, was found closely related to mammalian CLCA1, 3 and 4. In contrast, the second one, gCLCA2, seemed more closely related to mammalian CLCA2 than to gCLCA1 or mammalian CLCA1, 3 and 4. In this cumulative thesis, the galline CLCA genes and their genomic structures were analyzed and both members were cloned. Their protein architecture and biochemical properties were investigated in silico and in vitro. In addition, their mRNA as well as their cellular protein expression patterns were analyzed. All data were compared to mammalian CLCA1, 2, 3, and 4. Both avian proteins are encoded by 14 exons and are located in a conserved locus between the Outer Dense Fiber of Sperm Tails 2-Like (ODF2L) and SH3-Domain GRB2-Like Endophilin B1 (SH3GLB1) genes. gCLCA1 combines many properties of mammalian CLCA1, 3 and 4 as it was shown to be a cleaved protein with a typical CLCA domain architecture. Despite its relatively high phylogenetic distance to mammalian CLCA4, it shares most common traits with this member. This includes heavy asparagine-linked glycosylation, the presence of a transmembrane domain in the carboxy-terminal cleavage product and protein expression in the apical membrane of enterocytes. In contrast, gCLCA2 was highly similar to mammalian CLCA2 in terms of its protein architecture, cleavage and glycosylation. These findings were in line with results from in silico analyses of CLCA2 sequences from other avian species.Furthermore, the presence of a transmembrane domain in the carboxy-terminal cleavage product and its expression in keratinocytes are traits of avian CLCA2, which are also found in mammalian CLCA2. Interestingly, and as opposed to the expression patterns of mammalian CLCA proteins, no overlapping tissue or cellular expression patterns were detected for the two galline CLCA members. Based on these findings, CLCA2 appears to be highly conserved among birds and mammals. The results allow to speculate that a hypothetical gene ancestor was expressed in keratinocytes of a common ancestral species before mammalian and avian lineages diverged. This high degree of CLCA2 conservation is in contrast to gCLCA1 and mammalian CLCA1, 3 and 4. During evolution, a hypothetical ancient ancestor of gCLCA1 / mammalian CLCA1, 3, and 4, was likely expressed by enterocytes of a common ancestral species of mammals and birds. The hypothetical ancestral gene seems to have expanded by gene duplications in the mammalian lineage, which did not occur in birds. Besides that, these findings cannot only be used to unveil the evolutionary history of the CLCA family but should be taken into account with regard to the selection of an animal model for the functional analysis of these genes. The chicken might serve as a promising species for knockout models to study CLCA2 functions in vivo. Results obtained from such a knockout chicken are likely transferable to mammalian CLCA2 due to the high degree of conservation. A chicken gCLCA1 knockout model might provide data, which might be transferred most likely to mammalian CLCA4 genes in the gut, as both share a similar cell type specific protein expression in this microenvironment, a similar protein architecture as well as similar biochemical properties. At the transition to the post-genomic era with publically accessible information on gene structures as well as nucleotide and protein sequences of various species, comprehensive analyses of gene families across species have become possible. The comparison of such data in combination with the comparison of gene related information, including cellular expression patterns and biochemical properties, is a powerful approach to enlighten the evolutionary background of proteins. Furthermore, it might be beneficial to identify the most suitable animal model for further functional and biomedical studies.Die CLCA, engl. „chloride channel regulator, calcium-activated“ Genfamilie wird hauptsächlich mit Krebserkrankungen sowie chronisch entzündlichen Atemwegserkrankungen in Zusammenhang gebracht. Die mutmaßlich komplexen Funktionen dieser Gene sind bisher jedoch noch weitgehend unbekannt. Die CLCA Genfamilie umfasst bei Säugetieren vier verschiedene Cluster, die als CLCA1 bis CLCA4 bezeichnet werden. Sie zeichnet sich durch eine außerordentliche Komplexität und Vielfältigkeit aus und beinhaltet tierartlich variierend amplifizierte und inaktivierte Gene. So besitzt der Mensch beispielsweise drei intakte CLCAs sowie ein inaktiviertes Gen, wohingegen die Maus über 8 CLCAs verfügt, von denen ebenfalls eines als inaktiviertes Gen vorliegt. Darüber hinaus sind die Gewebe- und Zellexpressionsmuster der CLCA-Homologen auch innerhalb einer Spezies häufig redundant. Diese Komplexität und Redundanz von CLCA könnten Gründe sein, welche die Aufdeckung der Funktion dieser Genfamilie im Säugetiermodell bisher erschwerte. Damit stellen sich zwei Fragen: Ist die Komplexität dieser Genfamilie eine Eigenart der Säugetiere? Und was ist der evolutionäre Hintergrund für diese Entwicklungen? Um diese Fragen zu beantworten, werden Daten über CLCA benötigt, die von evolutionär weiter entfernten Arten stammen. Kürzlich wurde für das Huhn ein relativ einfacher CLCA Genlokus vorhergesagt, welcher nur zwei CLCA Gene umfasst. Das erste CLCA Genprodukt des Huhns, gCLCA1, zeichnet sich durch eine besondere phylogenetische Nähe zu CLCA1, 3 und 4 der Säugetiere aus. Im Gegensatz dazu ist das zweite CLCA Genprodukt, gCLCA2, näher mit Säuger-CLCA2 verwandt als mit gCLCA1 oder Säuger-CLCA1, 3 oder 4. In dieser kumulativen These wurden die gallinen CLCA Gene sowie deren genomische Struktur analysiert und beide Homologe wurden kloniert. Darüber hinaus wurde deren Proteinarchitektur und die biochemischen Eigenschaften in silico und in vitro untersucht. Weiterhin wurden die mRNA- und zellulären Proteinexpressionsmuster im Vergleich zu CLCA1, 2, 3 und 4 bei Säugetieren analysiert. Beide Vogelproteine werden von 14 Exons kodiert und befinden sich an einem konservierten Ort zwischen den ODF2L, engl. „Outer Dense Fiber of Sperm Tails 2-Like” und SH3GLB1, engl „SH3-Domain GRB2-Like Endophilin B1“ Genen. gCLCA1 vereint mit seiner Proteinspaltung sowie der Proteinarchitektur viele Eigenschaften von CLCA1, 3 und 4 der Säugetiere. Trotz einer relativ großen phylogenetischen Entfernung zu Säuger-CLCA4 weist es jedoch die meisten gemeinsamen Merkmale mit diesem CLCA-Vertreter auf. Hierzu zählen eine starke, an Asparagin gekoppelte Glykosylierung, eine Transmembrandomäne im carboxyterminalen Spaltprodukt und eine Proteinexpression in der apikalen Membran von Enterozyten. Im Gegensatz dazu ist gCLCA2 dem Säugetier-CLCA2 in Bezug auf dessen Phylogenie, Proteinarchitektur, Spaltung und Glykosylierung sehr ähnlich. Diese Befunde ließen sich mittels in silico Analysen auch für weitere aviäre CLCAs nachweisen. Daneben sind die Präsenz einer Transmembrandomäne im carboxyterminalen Spaltprodukt und die Expression in Keratinozyten Merkmale des aviären CLCA2, die auch bei Säugetier-CLCA2 vorzufinden sind. Bemerkenswerterweise fanden sich im Gegensatz zu den Säuger-CLCAs bei den gallinen CLCA-Mitgliedern keine überlappenden gewebe- und zellspezifischen Expressionsmuster. Unter Betrachtung dieser Befunde erscheint CLCA2 bei Vögeln und Säugetieren stark konserviert zu sein. Weiterhin lässt sich auf Basis der in dieser kumulativen These erhobenen Daten spekulieren, dass ein hypothetischer gemeinsamer genetischer Vorfahre wahrscheinlich in Keratinozyten eines gemeinsamen Vorfahren von Vögeln und Säugern exprimiert wurde. Dieser hohe Grad an Konservierung von CLCA2 steht im Gegensatz zu demjenigen von gCLCA1 und Säugetier-CLCA1, 3 und 4. Im Laufe der Evolution scheint ein hypothetischer genetischer Vorfahre von gCLCA1/Säugetier-CLCA1, 3 und 4 vermutlich in Enterozyten eines gemeinsamen Vorfahren von Vögeln und Säugern exprimiert worden zu sein. Dieser hypothetische genetische Vorfahre scheint durch Genduplikationen bei Säugetieren expandiert zu sein, nicht jedoch bei Vögeln. Neben diesen Aussagen zu einem wahrscheinlichen evolutionären Szenario der CLCA Genfamilie zwischen Vogel und Säuger lassen sich die Ergebnisse jedoch auch zur Auswahl eines Modellorganismus zur funktionalen Analyse dieser Gene nutzen. Hierbei erscheint das Huhn zur Untersuchung der CLCA2-Funktion in vivo ein vielversprechender Kandidat für knockout-Modelle, deren Untersuchungsergebnisse durch den Grad an Konservierung mit hoher Wahrscheinlichkeit auf Säugetiere übertragbar sind. Ein gCLCA1-Knockoutmodell könnte hingegen Daten liefern, die hochwahrscheinlich auf CLCA4 Gene von Säugetieren im Darm übertragbar sind, da beide in dieser anatomischen Lokalisation ein vergleichbares zellspezifisches Expressionsmuster sowie eine ähnliche Proteinarchitektur und biochemische Eigenschaften besitzen. Im Anbruch des postgenomischen Zeitalters, in dem Genstrukturen sowie Nukleotid- und Proteinsequenzen verschiedener Spezies öffentlich leicht zugänglich sind, werden umfassende, vergleichende Analysen von Genfamilien über verschiedene Spezies hinweg möglich. In Kombination mit dem Vergleich von genbezogenen Daten wie zellulären Expressionsmustern oder biochemischen Eigenschaften der Genprodukte ist dies ein wirkungsvolles Vorgehen, um den evolutionären Hintergrund von Proteinen aufzudecken und das geeignetste Tiermodell für weitere wissenschaftliche Fragestellung auszuwählen