Cellular Automaton in Dynamical Environment

Tato bakalářská práce se zabývá metodou evoluce celulárního automatu schopného sebeopravy po poškození vlivem externího prostředí. Popisovaná metoda je založená na algoritmu celulárního programování a využívá i principů biologického developmentu. V rámci této práce jsou provedeny experimenty vedoucí k ověření regeneračních schopností automatu vyvinutého za pomoci tohoto postupu.This bachelor thesis focuses on the method of evolution of cellular automaton capable of self-repair after being damaged by external environment. The described method is based on cellular programming algorithm and uses principles of biological development. Experiments leading to verification of regenerative ability for cellular automaton evolved by this approach are presented in this work.

Instruction-Controlled Cellular Automata

Tato práce se zabývá návrhem nového konceptu řízení celulárního automatu založeného na tzv. instrukcích. Instrukci lze chápat jako určité pravidlo ověřující stavy předem definované skupiny buněk v sousedství vyšetřované buňky, přičemž při splnění stanovené podmínky kladené na danou skupinu je její stav změněn dle daného předpisu. Jelikož je možné v rámci jednoho výpočetního kroku uvažovat sekvenci složenou z více instrukcí, přičemž každá instrukce může změnit stav centrální buňky ihned po své aplikaci, lze jejich posloupnost pokládat za určitou formu krátkého programu. Tento koncept je zároveň možné rozšířit o jednoduché operace aplikované na buněčné okolí a prováděné během interpretace jednotlivých instrukcí - příkladem takové operace může být řádkový nebo sloupcový posun. Výhoda použití instrukcí tkví v redukci vyhledávacího prostoru, neboť oproti obvykle používané tabulkové metodě není nutné prohledávat množinu všech možných konfigurací buněk v okolí, nýbrž pouze několik oblastí vymezených předpisy instrukcí. Zatímco skupiny vyšetřovaných buněk v rámci instrukce jsou navrhovány ručně na základě analýzy řešené úlohy, posloupnost jejich umístění v chromozomu je optimalizována prostřednictvím genetického algoritmu. Úspěšnost navržené metody řízení celulárního automatu je zkoumána na vybraných benchmarkových úlohách - majoritě, synchronizace, samoorganizaci a návrhu kombinačních logických obvodů.The thesis focuses on a new concept of cellular automata control based on instructions. The instruction can be understood as a rule that checks the states of cells in pre-defined areas in the cellular neighbourhood. If a given condition is satisfied, the state of the central cell is changed according to the definition of the instruction. Because it's possible to perform more instructions in one computational step, their sequence can be understood as a form of a short program. This concept can be extended with simple operations applied to the instruction's prescription during interpretation of the instructions - an example of such operation can be row shift or column shift. An advantage of the instruction-based approach lies in the search space reduction. In comparison with the table-based approach, it isn't necessary to search all the possible configurations of the cellular neighbouhood, but only several areas determined by the instructions. While the groups of the inspected cells in the cellular neighbourhood are designed manually on the basis of the analysis of the solved task, their sequence in the chromosome is optimized by genetic algorithm. The capability of the proposed method of cellular automata control is studied on these benchmark tasks - majority, synchronization, self-organization and the design of combinational circuits.

FireProt: web server for automated design of thermostable proteins

There is a continuous interest in increasing proteins stability to enhance their usability in numerous biomedical and biotechnological applications. A number of in silico tools for the prediction of the effect of mutations on protein stability have been developed recently. However, only single-point mutations with a small effect on protein stability are typically predicted with the existing tools and have to be followed by laborious protein expression, purification, and characterization. Here, we present FireProt, a web server for the automated design of multiple-point thermostable mutant proteins that combines structural and evolutionary information in its calculation core. FireProt utilizes sixteen tools and three protein engineering strategies for making reliable protein designs. The server is complemented with interactive, easy-to-use interface that allows users to directly analyze and optionally modify designed thermostable mutants. FireProt is freely available at http://loschmidt.chemi.muni.cz/fireprot.Web of Science45W1W399W39

FireProt: Web server for automated design of thermostable proteins

Stable proteins are used in numerous biomedical and biotechnological applications. Unfortunately, naturally occurring proteins cannot usually withstand the harsh industrial environment, since they are mostly evolved to function at mild conditions. Therefore, there is a continuous interest in increasing protein stability to enhance their industrial potential. A number of in silico tools for the prediction of the effect of mutations on protein stability have been developed recently. However, only single-point mutations with a small effect on protein stability are typically predicted with the existing tools and have to be followed by laborious protein expression, purification, and characterization. A much higher degree of stabilization can be achieved by the construction of the multiple-point mutants. Here, we present the FireProt method [1] and the web server [2] for the automated design of multiple-point mutant proteins that combines structural and evolutionary information in its calculation core. FireProt utilizes sixteen bioinformatics tools, including several force field calculations. Highly reliable designs of the thermostable proteins are constructed by two distinct protein engineering strategies, based on the energy and evolution approaches and the multiple-point mutants are checked for the potentially antagonistic effects in the designed protein structure. Furthermore, time demands of the FireProt method are radically decreased by the utilization of the smart knowledge-based filters, protocol optimization, and effective parallelization. The server is complemented with an interactive, easy-to-use interface that allows users to directly analyze and optionally modify designed thermostable proteins. The server is freely available at http://loschmidt.chemi.muni.cz/fireprot. 1. Bednar, D., Beerens, K., Sebestova, E., Bendl, J., Khare, S., Chaloupkova, R., Prokop, Z., Brezovsky, J., Baker, D., Damborsky, J., 2015: FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants. PLOS Computational Biology 11: e1004556. 2. Musil, M., Stourac, J., Bendl, J., Brezovsky, J., Prokop, Z., Zendulka, J., Martinek, T., Bednar, D., Damborsky, J., 2017, FireProt: Web Server for Automated Design of Thermostable Proteins, Nucleic Acids Research, in press, doi: 10.1093/nar/gkx285

Integration of Alzheimer’s disease genetics and myeloid genomics identifies disease risk regulatory elements and genes

Genome-wide association studies (GWAS) have identified more than 40 loci associated with Alzheimer’s disease (AD), but the causal variants, regulatory elements, genes and pathways remain largely unknown, impeding a mechanistic understanding of AD pathogenesis. Previously, we showed that AD risk alleles are enriched in myeloid-specific epigenomic annotations. Here, we show that they are specifically enriched in active enhancers of monocytes, macrophages and microglia. We integrated AD GWAS with myeloid epigenomic and transcriptomic datasets using analytical approaches to link myeloid enhancer activity to target gene expression regulation and AD risk modification. We identify AD risk enhancers and nominate candidate causal genes among their likely targets (including AP4E1, AP4M1, APBB3, BIN1, MS4A4A, MS4A6A, PILRA, RABEP1, SPI1, TP53INP1, and ZYX) in twenty loci. Fine-mapping of these enhancers nominates candidate functional variants that likely modify AD risk by regulating gene expression in myeloid cells. In the MS4A locus we identified a single candidate functional variant and validated it in human induced pluripotent stem cell (hiPSC)-derived microglia and brain. Taken together, this study integrates AD GWAS with multiple myeloid genomic datasets to investigate the mechanisms of AD risk alleles and nominates candidate functional variants, regulatory elements and genes that likely modulate disease susceptibility

Rescue of deficits by Brwd1 copy number restoration in the Ts65Dn mouse model of Down syndrome

With an incidence of ~1 in 800 births, Down syndrome (DS) is the most com- mon chromosomal condition linked to intellectual disability worldwide. While the genetic basis of DS has been identified as a triplication of chromosome 21 (HSA21), the genes encoded from HSA 21 that directly contribute to cognitive de fi cits remain incompletely understood. Here, we found that the HSA21- encoded chromatin effector, BRWD1, was upregulated in neurons derived from iPS cells from an individual with Down syndrome and brain of trisomic mice. We showed that selective copy number restoration of Brwd1 in trisomic animals rescued de fi cits in hippocampal LTP, cognition and gene expression. We demonstrated that Brwd1 tightly binds the BAF chromatin remodeling complex, and that increased Brwd1 expression promotes BAF genomic mistargeting. Importantly, Brwd1 renormalization rescued aberrant BAF localization, along with associated changes in chromatin accessibility and gene expression. These findings establish BRWD1 as a key epigenomic mediator of normal neurodevelopment and an important contributor to DS-related phenotypes

System for functional annotation of single nucleotide polymorphisms

Single nucleotide polymorphisms are the substitution of one nucleotide in the DNA sequence that may or may not have phenotypic consequences. Here we describe a new system for ranking non-synonymous protein substitutions by their deleterious effects. The computational core of the proposed system is based on a rational combination of the results from the selected subset of publicly available tools. The weight coefficients for the individual tools are calculated on the basis of their confidence score and their reliabilities are assigned accordingly to their performance measured on the extensive dataset. The validation of the performance on the dataset consisting of 5 000 substitutions shows that overall accuracy of the system was improved by 6% in comparison to the simple majority vote

Dilemmas of Teacher Authority

The article deals with teacher authority from the point of view of dilemmas it can cause when used in education. In the first part authors try to define the term dilemma in association with authority by comparing it to antinomy. The work then introduces several approaches to teacher authority dilemmas, including the ones of Fromm, Fink and other renowned scholars. Further, dilemmas associated with exercising of teacher authority are presented using examples from current research dealing with this phenomenon. The authors also present results of two of their recent surveys focusing on student teachers’ understanding of teacher authority dilemmas and teacher interaction styles that may cause them. Based on the literature and research authors in the last part of their article show most common and controversial teacher dilemmas related to the use of authority

PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions

<div><p>An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools’ predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To enable comprehensive evaluation of variants, the predictions are complemented with annotations from eight databases. The web server is freely available to the community at <a href="http://loschmidt.chemi.muni.cz/predictsnp2" target="_blank">http://loschmidt.chemi.muni.cz/predictsnp2</a>.</p></div

Performance of nucleotide-based and protein-based prediction tools and their consensuses, evaluated using the dataset of variants associated with Mendelian diseases.

<p>(A) Observed normalized accuracy and (B) area under the receiver operating characteristic curve (AUC) values are shown as blue and red bars for nucleotide- and protein-based tools and their consensuses, respectively. The horizontal dashed lines represent average performance values for each tool type.</p