Artificial Intelligence for Game Playing

Práce se zabývá metodami umělé inteligence aplikovanými pro hraní strategických her, ve kterých probíhá veškerá interakce v reálném čase (tzv. real-time strategic - RTS). V práci se zabývám zejména metodu strojového učení Q-learning založenou na zpětnovazebním učení a Markovovu rozhodovacím procesu. Praktická část práce je implementována pro hraní hry StarCraft: Brood War.Mnou navržené řešení, implementované v rámci pravidel soutěže SSCAIT, se učí sestavit optimální konstrukční pořadí budov dle hracího stylu oponenta. Analýza a vyhodnocení systému jsou provedeny srovnáním s ostatními účastníky soutěže a rovněž na základě sady odehraných her a porovnání počátečního chování s výsledným chováním natrénovaným právě na této sadě.The focus of this work is the use of artificial intelligence methods for a playing of real-time strategic (RTS) games, where all interactions of players are performed in real time (in parallel). The thesis deals mainly with the use of machine learning method Q-learning, which is based on reinforcement learning and Markov decision process. The practice part of this work is implemented for StarCraft: Brood War game.A proposed solution learns to make up an optimal order of buildings construction in respect to a playing style (strategy) of the opponent(s). The solution is proposed within the rules of the SSCAIT tournament. Analysis and evaluation of the proposed system are based on a comparison with other participants of the competition as well as a comparison of the system behavior before and after the playing of a set of the games.

Analysis of Gene Expression Omnibus Leukaemia Data from the Illumina HumanMethylation450 Array

<p>DNA methylation has recently been emerging as an important feature of cancer1. Changes in the methylation of genes and their promoters can cause a change of gene expression that may result in oncogenesis. Several types of leukaemia are known to have mutations in genes involved in DNA methylation2,3. Study of genome-wide DNA methylation patterns may lead to new insights into the development of leukaemia. Public availability of genomic data allows for meta studies with samples sizes that would not be possible without the sharing of data between research groups. The Gene Expression Omnibus (GEO) represents a vast quantity of data for large-scale research including many studies on DNA methylation and cancer, and specifically leukaemia.</p> <p>For our study we will compare the methylation patterns in Acute Promyelocytic Leukemia (APL) and Acute Lymphoblastic Leukemia (ALL) to each other and to control samples. We hope to identify biologically relevant changes in CpG island level methylation that could relate to phenotypic differences seen between APL and ALL.</p

Additional file 3: Table S3. of Epigenetic modifying enzyme expression in asthmatic airway epithelial cells and fibroblasts

Comparison of epigenetic modifier gene expression between epithelial cells and fibroblasts from healthy donors. (DOCX 17 kb

Additional file 1: Table S1. of Epigenetic modifying enzyme expression in asthmatic airway epithelial cells and fibroblasts

Epigenetic modification genes including family, full name, and alias. (DOCX 19 kb

Variation in RNA-Seq Transcriptome Profiles of Peripheral Whole Blood from Healthy Individuals with and without Globin Depletion

<div><p>Background</p><p>The molecular profile of circulating blood can reflect physiological and pathological events occurring in other tissues and organs of the body and delivers a comprehensive view of the status of the immune system. Blood has been useful in studying the pathobiology of many diseases. It is accessible and easily collected making it ideally suited to the development of diagnostic biomarker tests. The blood transcriptome has a high complement of globin RNA that could potentially saturate next-generation sequencing platforms, masking lower abundance transcripts. Methods to deplete globin mRNA are available, but their effect has not been comprehensively studied in peripheral whole blood RNA-Seq data. In this study we aimed to assess technical variability associated with globin depletion in addition to assessing general technical variability in RNA-Seq from whole blood derived samples.</p><p>Results</p><p>We compared technical and biological replicates having undergone globin depletion or not and found that the experimental globin depletion protocol employed removed approximately 80% of globin transcripts, improved the correlation of technical replicates, allowed for reliable detection of thousands of additional transcripts and generally increased transcript abundance measures. Differential expression analysis revealed thousands of genes significantly up-regulated as a result of globin depletion. In addition, globin depletion resulted in the down-regulation of genes involved in both iron and zinc metal ion bonding.</p><p>Conclusions</p><p>Globin depletion appears to meaningfully improve the quality of peripheral whole blood RNA-Seq data, and may improve our ability to detect true biological variation. Some concerns remain, however. Key amongst them the significant reduction in RNA yields following globin depletion. More generally, our investigation of technical and biological variation with and without globin depletion finds that high-throughput sequencing by RNA-Seq is highly reproducible within a large dynamic range of detection and provides an accurate estimation of RNA concentration in peripheral whole blood. High-throughput sequencing is thus a promising technology for whole blood transcriptomics and biomarker discovery.</p></div

Additional file 4: of Altered DNA methylation is associated with aberrant gene expression in parenchymal but not airway fibroblasts isolated from individuals with COPD

Figure S2. (.EPS): GRIK2 methylation and expression do not correlate with smoking pack-years or smoking status. A) Correlation plot of GRIK2 cg16006558 methylation with smoking pack years. B) Correlation plot of GRIK2 expression with smoking pack-years. Neither CpG methylation nor gene expression correlates with smoking pack-years. C) GRIK2 expression separated by smoking status. D) GRIK2 CpG methylation separated by smoking status. Smoking status does not drive alterations to GRIK2 DNA methylation or gene expression. (EPS 2269 kb

Additional file 3: of Altered DNA methylation is associated with aberrant gene expression in parenchymal but not airway fibroblasts isolated from individuals with COPD

Figure S1. (.EPS): CpG methylation variation in parenchymal fibroblasts in COPD samples. A) Plot of the difference in methylation standard deviation of samples from donors with COPD and donors without COPD at the 359 CpGs differentially variably methylated between samples from donors with COPD and donors without COPD. B) Representation of the CpG type with which DVPs were associated versus CpG types of all CpGs included in the analysis. (EPS 1922 kb

Experimental design.

<p>Experimental design.</p

Globin depletion yields 3500 additional robustly detectable transcripts from a single representative peripheral whole blood RNA-Seq experiment.

<p>(A) Correlation plot of the transcript FPKMs of an exemplar biological sample, either globin depleted (y-axis) or not (x-axis). (B) Distribution of transcript FPKMs in the same exemplar biological sample, either globin depleted (blue) or not (red). Data is shown on a log scale. Significant FPKM cutoffs of 1, 2.5 and 1000 are marked by dashed line.</p

Globin depletion has no impact on the correlation of technical replicates.

<p>Correlation plot of the transcript FPKMs of lane technical replicate (top) or pooled technical replicate (bottom) exemplar pairs. Data is shown on a log scale. Spearman's <i>rho</i> is reported for all (<i>r</i>_all) or reliably detectable transcripts (<i>r</i>_FPKM≥1) only.</p