55 research outputs found

    RNA-based next generation sequencing approaches in HLA genotyping and HLA expression quantification

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    The advent of next generation sequencing (NGS) technologies has changed the nature of human leukocyte antigen (HLA) research. Thanks to its increased sequencing throughput, NGS empowers high-accuracy HLA genotyping in clinical settings, disease association studies, and the development of potential future immunotherapeutics. Current NGS can be divided into two different approaches. Illumina’s technology with massively parallel sequencing produces a high number of short reads. Illumina provides highly accurate data with a minimal number of sequencing errors; however, the short reads can cause issues with alignment and phasing in HLA genotyping. In contrast, the long-read technologies, Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio), offer a single-molecule sequencing approach enabling sequencing of ultra-long reads. However, these two suffer from higher error rates, making HLA genotyping potentially less accurate. Concurrently with the development of NGS applications, several bioinformatics software have been developed for assigning HLA alleles based on existing genomic and RNA sequencing (RNA-seq) data and for imputing HLA alleles using single-nucleotide polymorphism (SNP) markers. In addition to HLA genotyping, NGS provides a powerful tool for studying the expression of several HLA genes and alleles in multiple samples simultaneously, replacing more conventional methods such as quantitative PCR (qPCR) and microarray. At the beginning of this thesis, earlier studies had already identified associations between differential HLA gene- and allele-level expression and human diseases. However, an RNA-seq method providing accurate and multiplexed way to study HLA gene- and allele-specific expression was lacking. To study comprehensively HLA gene- and allele-specific expression in normal peripheral blood mononuclear cells (PBMCs), a highly multiplexed RNA-seq method for Illumina using unique molecular identifiers (UMIs) in expression quantification was developed in study I. The combination of a personalized HLA reference and an in-house pipeline, written in R, allowed an extensive comparison of HLA gene and allotype expression in PBMC samples of 50 individuals. The results showed that although the expression in HLA was clearly gene- and allele-specific, there was also variation within genes and alleles representing the differential expression between individuals. Additionally, study I revealed haplotype-specific expression of six common Finnish HLA haplotypes. Interestingly, two autoimmune haplotypes, which have been associated with e.g. celiac disease and type I diabetes, had very distinct expression levels suggesting that the level of haplotype expression alone is not the primary predisposing factor. In study II, a targeted RNA-based method was developed for HLA ONT sequencing. The method employed PCR-based enrichment and barcoding, enabling 10 samples and several HLA genes to be multiplexed and sequenced in a single sequencing run. By using the MinION sequencer together with SpotOn flow cells, a sufficient number of reads per sample for HLA genotyping was generated. To achieve the best possible genotyping accuracy, only the higher quality 2D reads were included in the analysis. Despite the sequencing errors that ONT introduces during sequencing, the HLA genotyping results were obtained in 80% of HLA class I alleles and 95% of HLA class II alleles. Since HLA has a crucial role in immune surveillance and in the initiation of antitumor immune responses, the aim of study III was to investigate HLA expression in tumor samples acquired from a longitudinal high-grade serous ovarian cancer (HGSC) cohort. The sample material consisted of ovarian tumors and various intra-abdominal anatomical sites collected prior and after chemotherapy. In the inter-tissue analysis, differential expression levels in mainly non-classical HLA genes were found between distinct anatomical sites, indicating tissue-specific HLA expression levels. Additionally, the results in study III showed that in one of the anatomical sites, omentum, chemotherapy altered the expression of class II. Interestingly, the intra-patient analysis revealed that the allelic imbalance between two heterozygous alleles changed in the samples acquired from different tissues and treatment phases. To conclude, this thesis provides novel insights into gene- and allele-level HLA expression in different tissues. Additionally, it introduces new RNA-based methods for HLA genotyping and HLA expression quantification, which can be applied in future studies. Finally, it provides a comprehensive review of methods and bioinformatics tools designed for HLA allele-specific expression and the diseases associated with differential HLA allele expression.Uuden sukupolven sekvensointimenetelmät ovat muuttaneet HLA-tutkimuksen luonteen. Nämä korkean suoritustehon sekvensointimenetelmät mahdollistavat tänä päivänä tarkemman HLA-genotyypityksen, tautiassosiaatiotutkimukset sekä uusien immunoterapioiden kehittämisen. Uuden sukupolven sekvensointimenetelmät jaetaan tavallisesti kahteen luokkaan. Illuminan sekvensointiteknologia tarjoaa tarkemman sekvensointituloksen, mutta sen tuottamat lyhyet sekvensointifragmentit aiheuttavat linjausongelmia HLA-genotyypityksessä. Sen sijaan Oxford Nanopore - ja PacBio-sekvensointiteknologiat mahdollistavat erittäin pitkien molekyylien sekvensoimisen yhtenä fragmenttina. Ne kuitenkin tuottavat enemmän sekvensointivirheitä, mikä voi huonontaa genotyypitystulosten tarkkuutta. Uusien sekvensointimenetelmien kehittymisen lisäksi myös uusien genomisen ja RNA-pohjaisen datan HLA-genotyypitykseen sekä HLA-imputaatioon tarkoitettujen laskennallisten työkalujen määrä on kasvanut. Uuden sukupolven sekvensointimenetelmät tarjoavat myös tehokkaan työkalun useiden näytteiden HLA geeni- ja alleelitason ekspression samanaikaiseen määrittämiseen korvaten aiemman kvantitatiivisen PCR-menetelmän ekspression tutkimisessa. Ennen väitöskirjatutkimuksen aloittamista, aiemmissa tutkimuksissa oli jo saatu viitteitä HLA-geeni- ja alleeliekspression vaikutuksesta useissa eri taudeissa. Saatavilla ei kuitenkaan ollut RNA-sekvensointimenetelmää, joka olisi mahdollistanut tarkan HLA-geeni- ja alleelitason ekspression määrittämisen useista näytteistä samanaikaisesti. HLA geeni- ja alleelispesifisen ekspression tutkimisen mahdollistamiseksi veren mononukleaarisoluista, tutkimuksessa I kehitettiin useiden näytteiden samanaikaiseen sekvensointiin tarkoitettu RNA-sekvensointimenetelmä, joka hyödyntää uniikkeja molekyylitunnisteita ekspression määrittämisessä. Näytekohtaisen HLA-referenssin käyttäminen yhdessä R-komentokieleen perustuvan analyysityökalun kanssa mahdollisti HLA geeni- ja alleelispesifisen ekspression vertaamisen ääreisveren mononukleaarisoluissa 50 verenluovuttajan välillä. Tutkimus I:n tulokset paljastivat, että vaikka ekspressiotaso eri HLA-geenien ja -alleelien välillä oli selvästi geeni- ja alleelispesifistä, ekspressioprofiileissa oli myös vaihtelua geenien ja alleelien sisällä indikoiden verenluovuttajien välisiä eroja. Tutkimus I:n tulokset osoittivat myös HLA-ekspression vaihtelevan kuuden suomalaisilla yleisen HLA-haplotyypin välillä. Kaksi aiemmin keliakiaan ja tyypin 1 diabetekseen yhdistettyä haplotyyppiä sijoittuivat ekspressiovertailussa kauimmaksi toisistaan. Näin ollen näyttäisi, ettei HLA-haplotyyppien ekspressiotasot ole näille taudeille altistava tekijä. Tutkimuksessa II kehitettiin HLA-geeneille kohdennettu RNA-pohjainen menetelmä Oxford Nanopore-sekvensointialustalle. Menetelmässä HLA-geenit rikastettiin komplementaarisesta DNA:sta PCR:n avulla. Monistettuihin HLA-molekyyleihin lisättiin näytekohtaiset tunnisteet, joka mahdollisti kymmenen näytteen ja useiden HLA-geenien samanaikaisen sekvensoinnin yhdessä sekvensointiajossa. Sekvensointi MinION-laitteella ja SpotON-virtauskennoilla tuotti tyydyttävän määrän sekvenssifragementteja näytettä kohden. Mahdollisimman tarkan HLA-genotyypitystuloksen varmistamiseksi tyypityksessä käytettiin ainoastaan Nanoporen korkeampilaatuisia 2D-sekvenssifragmentteja. Huolimatta Oxford Nanopore -teknologian sekvensoinnin aikana tapahtuvista sekvensointivirheistä, HLA-tyypitystulos saatiin 80%.lla HLA:n luokka I -alleeleista ja 95%:lla luokka II -alleeleista. Koska HLA:lla on elintärkeä rooli immuunijärjestelmän monitoroimisessa ja anti-tuumorivälitteisen vasteen aikaansaamisessa, haluttiin tutkimuksessa III tutkia syöpänäytteiden HLA-geenien ilmenemistä. Osatyössä III käytettiin näytemateriaalina huonosti erilaistuneeseen seroosiin munasarjasyöpään sairastuneiden potilaiden näytteitä, jotka olivat kerätty sekä munasarjakudoksesta että useista eri muista kiinteistä kudoksista sekä askites-nesteestä ennen ja jälkeen kemoterapian. Vertailu eri kudosten välillä paljasti HLA-ekspression vaihtelevan eri kudosten välillä ja näin ollen olevan kudosspesifiä. Lisäksi tulokset osoittivat kemoterapian muokkaavan HLA-ekspressiota tietyissä kudoksissa. Mielenkiintoinen tulos saatiin vertaamalla saman potilaan eri kudoksista ja hoitovaiheista otettujen näytteiden HLA:n alleelispesifistä ekspressiota kahden alleelin välillä heterotsygooteissa alleelipareissa. Tulokset paljastivat, että osalla potilaista ekspressiosuhde kahden HLA-alleelin välillä muuttuu kudosten ja hoitovaiheiden mukaan. Yhteenvetona voidaan todeta, että väitöskirja tarjoaa uusia näkökulmia kudoksen ja kemoterapian vaikutuksesta HLA:n geeni- ja alleelispesifiseen ekspressioon. Lisäksi väitöskirjassa esitellään uusia RNA-sekvenointiin perustuvia menetelmiä HLA-genotyypitykseen ja HLA-ekspression määrittämiseen, joita voidaan hyödyntää tulevissa tutkimuksissa. Lopuksi väitöskirja tarjoaa kattavan katsauksen HLA:n alleelispefisen ekspression tutkimukseen käytettävistä menetelmistä ja analyysityökaluista sekä HLA-ekspression ja sairauksien raportoiduista yhteyksistä

    Qualitative Analyse und Modellierung des wissenschaftlichen Arbeitens

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    Diese Masterarbeitet bietet einen Überblick der bestehenden Literatur zum Stand der Digitalisierung des geisteswissenschaflichen Arbeitens und den Stellenwert des Exzerpierens und Notierens während der Forschung. Die Erkentnisse aus der Literatur werden durch eine Interviewreihe, ausgewertet auf Basis der Grounded Theory, bestätigt. Basierend auf elf Interviews mit Promovierenden und Masterstudierenden wird ein informelles Aktitivätenmodell des (geistes)wissenschafltichen Arbeitens erstellt. Unter Miteinbeziehung des Forschungsstands auf dem Gebiet des Personal Information Management wird anschließend ein Concurrent Task Tree Modell für digitale Assistenz im Rahmen geisteswissenschaftlicher Forschung vorgestellt. Basierend darauf wurde ein Prototyp zur Evaluierung einer stillen Ausführungs- und Übersetzungsassistenz entwickelt, der im Labor getestet wurde. Die Nutzung des Prototypen führte entgegen der Erwartung zu keiner Effizienzsteigerung beim Zusammenfassen einer Textquelle. Gleichzeitig konnet aber bestätigt werden, dass die Nutzung eines Eye-Trackers und einer Webcam die Verortung von Papiernotizen im digitalen Quelltext ermöglicht. Bei die Auswertung der Interviews wurden zudem zwei Typen der Literaturverwaltung beobachtet, die den Stellenwert von Exzerpten unterstreichen und die zukünftige Entwicklung von Literaturverwaltungssoftware für Geisteswissenschaftler beeinflussen sollten

    차세대 시퀀싱 데이터에 대한 SNV/InDel 호출 및 하플로타이핑의 새로운 접근 방법

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    학위논문 (박사) -- 서울대학교 대학원 : 공과대학 전기·컴퓨터공학부, 2021. 2. 박근수.차세대 시퀀싱 데이터에 대한 수많은 변이 호출 알고리즘이 개발되어 왔다. 대다수 변이 호출 알고리즘은 신뢰할 수 있지만 추가적인 성능 향상을 위한 여지는 남아있다. 특히, 낮은 리드 깊이를 가지는 데이터에 대한 변이 호출과 체세포 변이 호출은 개선될 여지가 많다. 첫 번째로, 본 논문에서는 위 양성 변이를 제거하여 변이 호출의 정밀도를 개선하는 새로운 알고리즘인 RDscan을 제안한다. RDscan은 잘못 정렬된 리드를 제거하고 리드를 재배치 한 후, 리드 깊이 분포에 기반한 변이의 신뢰도 점수를 계산하여 위 양성 변이를 제거한다. 우리는 최신 변이 호출 알고리즘들을 사용하여 RDscan의 성능을 평가하였다. 1000 게놈 프로젝트와 일루미나의 데이터세트에 대하여 RDscan을 통한 추가적인 변이 필터링은 테스트에 사용된 대부분의 변이 호출 알고리즘의 정확성을 개선시켰다. 생식세포 변이에 대한 호출은 12건의 테스트 중 11건, 체세포 변이 대한 호출은 24건의 테스트 중 21건에서 정확성이 증가되었다. 알려진 골드 스탠다드 변이 세트를 사용하여 각 알고리즘의 파라미터 최적화를 통해 생성된 최적의 변이 세트에 대해서도, RDscan 은 생식세포 변이에 대한 12건 중 5건, 체세포 변이에 대한 24 건 중 21건에서 변이 호출 정확성을 개선하였다. 임상 및 연구에서는 단일 게놈 가닥에 존재하는 변이의 세트 정보 (하플로타이핑)를 필요로 하는 경우가 있다. 특히 인간 백혈구 항원 유전자들에 대한 하플로타이핑은 실제 임상에서 다루는 중요한 문제이다. 기존 연구들은 차세대 시퀀싱 기반 알고리즘이 인간 백혈구 항원 유전자에 대한 하플로타이핑을 수행하기에 적합함을 보여주었다. 하지만, 하플로타이핑의 정확성을 저하시키는 대립 유전자의 상 조정 문제를 해결한 알고리즘은 없다. 두 번째로, 본 논문에서는 차세대 시퀀싱 데이터로부터 인간 백혈구 항원 유전자들에 대한 하플로타이핑을 수행하는 새로운 알고리즘인 HLAscan을 소개한다. HLAscan은 ImMunoGeneTics 프로젝트에서 제공하는 IMGT/HLA 데이터베이스의 인간 백혈구 항원 유전자 서열들에 대해 개인의 유전체 리드를 정렬한다. 그 후, 정렬된 리드의 분포에 기반한 점수를 사용하여 올바른 대립유전자의 상을 결정할 수 있다. HLAscan을 통한 하플로타이핑은1000 게놈 프로젝트와 HapMap 프로젝트의 공식 데이터세트에 대해서 기존의 차세대 시퀀싱 기반 알고리즘들보다 높은 정확성을 보여주었다. 또한 HiSeq X-TEN으로 생성한 아홉 가족의 데이터세트에 대해서, HLAscan을 사용한 하플로타이핑 결과는 96.9%의 정확성을 보였고, 그 중 90× 이상의 높은 리드 깊이를 가지는 데이터세트에 대해서는 100% 정확성을 보였다.Several tools have been developed for calling variants from next-generation sequencing data. Although they are generally accurate and reliable, most of them have room for improvement, especially in regard to calling variants in datasets with low read depth coverage. In addition, the somatic variants predicted by several somatic variant callers tend to have very low concordance rates. First, we propose a new tool (RDscan) for improving germline and somatic variant calling in next-generation sequencing data. RDscan removes misaligned reads, repositions reads, and calculates RDscore based on the read depth distribution. With RDscore, RDscan improves the precision of variant callers by removing false variants. When we tested our new tool using the latest variant calling algorithms, accuracy was improved for most of the algorithms. After screening variants with RDscan, calling accuracies increased for germline variants in 11 out of 12 cases and for somatic variants in 21 out of 24 cases. For the best set of variants produced by optimizing the parameters of each algorithm using the known truth sets, RDscan increased the calling accuracies for germline variants in 5 out of 12 cases and for somatic variants in 21 out of 24 cases. Some applications require information on multiple variants in a single genome strand (haplotyping). In particular, precise haplotyping for human leukocyte antigen genes is of great clinical importance. Several recent studies showed that next-generation sequencing based method is a feasible and promising technique for haplotyping of human leukocyte antigen genes. To date, however, no method with sufficient read depth has completely solved the allele phasing issue. Second, we developed a new method (HLAscan) for HLA haplotyping using NGS data. HLAscan performs alignment of reads to HLA sequences from human leukocyte antigen (IMGT/HLA) database in the international ImMunoGeneTics project. The distribution of aligned reads was used to calculate a score function to determine correctly phased alleles by progressively removing false-positive alleles. Comparative HLA typing tests using public datasets from the 1000 Genomes Project and the International HapMap Project demonstrated that HLAscan could perform HLA typing more accurately than previously reported NGS-based methods. We also applied HLAscan to a family dataset with various coverage depths generated on the Illumina HiSeq X-TEN platform. HLAscan identified allele types of HLA-A, -B, -C, -DQB1, and -DRB1 with 100% accuracy for sequences at ≥ 90× depth, and the overall accuracy was 96.9%.Abstract i Contents iii List of Figures iv List of Tables vii Chapter 1 Introduction 1 1.1 Background 1 1.2 Problem Statement 7 1.3 Previous Works and New Results 8 1.4 Organization 10 Chapter 2 SNV and InDel Calling 11 2.1 Preliminaries 11 2.2 Germline Variant Calling Algorithm 16 2.3 Somatic Variant Calling Algorithm 21 2.4 Results 22 2.5 Discussions 46 Chapter 3 Haplotyping for MHC region 48 3.1 Preliminaries 48 3.2 Haplotyping Algorithm 52 3.3 Results 58 3.4 Discussions 72 Chapter 4 Conclusion 74 4.1 Summary 74 4.2 Future Directions 76 Bibliography 78Docto

    Navigating Haystacks at 70 mph: Intelligent Search for Intelligent In-Car Services

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    ABSTRACT With an explosion of in-car services, it has become not only difficult but unsafe for drivers to search and access large amounts of information using current interaction paradigms. In this paper, we present a novel approach for visualizing and exploring search results, and the potential benefits of its application to the current in-car environment. We have iteratively developed and tested a prototype system that enables the seamless and personalized exploration of information spaces. In a number of eye-tracking studies, we analyzed user satisfaction and task performance for factual and explorative search tasks. We found that most participants were faster, made fewer errors and found the system easier to use than traditional ones. We believe that this approach would improve the traditional in-car interfaces -to search and access large number of services with rich information. This would reduce driver inattention to the road and improve road safety

    Sequence analysis methods for the design of cancer vaccines that target tumor-specific mutant antigens (neoantigens)

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    The human adaptive immune system is programmed to distinguish between self and non-self proteins and if trained to recognize markers unique to a cancer, it may be possible to stimulate the selective destruction of cancer cells. Therapeutic cancer vaccines aim to boost the immune system by selectively increasing the population of T cells specifically targeted to the tumor-unique antigens, thereby initiating cancer cell death.. In the past, this approach has primarily focused on targeted selection of ‘shared’ tumor antigens, found across many patients. The advent of massively parallel sequencing and specialized analytical approaches has enabled more efficient characterization of tumor-specific mutant antigens, or neoantigens. Specifically, methods to predict which tumor-specific mutant peptides (neoantigens) can elicit anti-tumor T cell recognition improve predictions of immune checkpoint therapy response and identify one or more neoantigens as targets for personalized vaccines. Selecting the best/most immunogenic neoantigens from a large number of mutations is an important challenge, in particular in cancers with a high mutational load, such as melanomas and smoker-associated lung cancers. To address such a challenging task, Chapter 1 of this thesis describes a genome-guided in silico approach to identifying tumor neoantigens that integrates tumor mutation and expression data (DNA- and RNA-Seq). The cancer vaccine design process, from read alignment to variant calling and neoantigen prediction, typically assumes that the genotype of the Human Reference Genome sequence surrounding each somatic variant is representative of the patient’s genome sequence, and does not account for the effect of nearby variants (somatic or germline) in the neoantigenic peptide sequence. Because the accuracy of neoantigen identification has important implications for many clinical trials and studies of basic cancer immunology, Chapter 2 describes and supports the need for patient-specific inclusion of proximal variants to address this previously oversimplified assumption in the identification of neoantigens. The method of neoantigen identification described in Chapter 1 was subsequently extended (Chapter 3) and improved by the addition of a modular workflow that aids in each component of the neoantigen prediction process from neoantigen identification, prioritization, data visualization, and DNA vaccine design. These chapters describe massively parallel sequence analysis methods that will help in the identification and subsequent refinement of patient-specific antigens for use in personalized immunotherapy

    Re-finding Tweets - Analyse der Personal-Information-Management-Praktik Re-finding im Kontext der Social-Media-Plattform Twitter

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    Diese Arbeit untersucht das Informationsverhalten von Social-Media-Anwendern aus der Perspektive des Personal Information Management und fokussiert dabei auf Re-finding-Verhalten, also das Wiederfinden von bereits wahrgenommener Information. Als Untersuchungsgegenstand dient die Social-Media-Plattform Twitter. Ziel der Arbeit ist die Beobachtung, Dokumentation, Beschreibung und Interpretation des Nutzerverhaltens beim Wiederfinden von Tweets und die Erarbeitung von Designvorschlägen, um Twitter-Nutzer bei diesem Informationsbedürfnis zu unterstützen. Als Forschungsstrategie dient ein Sequential-Mixed-Methods-Design, welches die sukzessive Erhebung und Auswertung von qualitativen bzw. subjektiven und quantitativen bzw. objektiven Daten in Form von zwei großen Studien --- einer Umfrage und einer Logstudie --- ermöglicht und es schließlich erlaubt, durch Kombination und Diskussion der Einzelergebnisse ein holistisches Bild von Wiederfindensverhalten auf Twitter zu zeichnen. Die Arbeit zeigt, dass Nutzer sehr häufig das Bedürfnis haben, zu bereits gesehenen Tweets zurückzukehren. Twitter, obwohl es einen Fokus auf Echtzeitinformationen legt, besitzt Archivcharakter, da häufig auch ältere Nachrichten wieder aufgerufen werden und persönliche Tweets einen längeren Lebenszyklus besitzen, als man dies von ihnen erwarten würde. Wiederfindensstrategien --- besonders Orienteering-Verhalten --- die bereits in anderen Personal-Information-Management-Kontexten wie mit E-Mails oder bei der Nutzung von Dateimanagern identifiziert werden konnten, treten auch beim Wiederfinden von Tweets auf. Wiederfinden kann eine komplexe Aufgabe sein, die Nutzer frustriert zurücklässt. Darüber hinaus haben Nutzer Schwierigkeiten bei der Einschätzung, ob Tweets in Zukunft von Relevanz sein könnten. Angemessen trainierte Algorithmen können Nutzer beim Wiederfinden von Tweets unterstützen

    ‘As if it was something spoken by a friend’: Political Public Relations and Digital Vote-canvassing Networks via Facebook during the 2013 Bangkok Gubernatorial Election Campaign

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    Social networking sites (SNSs) are an emerging channel of political mediation in Thailand for political figures to establish and develop their relationships with Thai citizens. Through focusing on the online political public relations work by candidates (and their teams) in the 2013 Bangkok gubernatorial election campaign, this thesis contributes a Thai perspective and experience to the growing literature on the use of SNSs globally in election campaigning. This research utilises multimodal textual analysis and interviews with Thai politicians, candidates and public relations personnel to explore the management of candidates’ images on Facebook via photographs, text and interactions, the management relationship between candidates and public relations personnel and citizens, the dynamics of what can be understood as ‘digital vote-canvassing networks’, and the various associated possibilities and challenges of using SNSs to contest for political power in the Thai context. This thesis finds that the political public relations work carried out via Facebook during the 2013 election campaign constituted a new and complex process of managing content and of managing human resources and relationships. The construction of candidates’ political images integrated existing Thai archetypes and connotations with more global images and strategies. The publication of campaign content on Facebook over the entire election campaign was managed to facilitate followers’ interpretations of the candidates’ campaigns. Election campaigns on Facebook developed digital vote-canvassing networks as candidates and their teams used different tactics to engage, interact with and manage citizens, as well as attempt to maximise the ‘spreadability’ of their content and thus extend their reach. As candidates campaigned on Facebook under election campaign rules not defined particularly for Facebook, the decentralisation of interaction among Facebook users was a major concern in controlling their election campaign on Facebook

    HLAProfiler utilizes k-mer profiles to improve HLA calling accuracy for rare and common alleles in RNA-seq data

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    BACKGROUND: The human leukocyte antigen (HLA) system is a genomic region involved in regulating the human immune system by encoding cell membrane major histocompatibility complex (MHC) proteins that are responsible for self-recognition. Understanding the variation in this region provides important insights into autoimmune disorders, disease susceptibility, oncological immunotherapy, regenerative medicine, transplant rejection, and toxicogenomics. Traditional approaches to HLA typing are low throughput, target only a few genes, are labor intensive and costly, or require specialized protocols. RNA sequencing promises a relatively inexpensive, high-throughput solution for HLA calling across all genes, with the bonus of complete transcriptome information and widespread availability of historical data. Existing tools have been limited in their ability to accurately and comprehensively call HLA genes from RNA-seq data. RESULTS: We created HLAProfiler ( https://github.com/ExpressionAnalysis/HLAProfiler ), a k-mer profile-based method for HLA calling in RNA-seq data which can identify rare and common HLA alleles with > 99% accuracy at two-field precision in both biological and simulated data. For 68% of novel alleles not present in the reference database, HLAProfiler can correctly identify the two-field precision or exact coding sequence, a significant advance over existing algorithms. CONCLUSIONS: HLAProfiler allows for accurate HLA calls in RNA-seq data, reliably expanding the utility of these data in HLA-related research and enabling advances across a broad range of disciplines. Additionally, by using the observed data to identify potential novel alleles and update partial alleles, HLAProfiler will facilitate further improvements to the existing database of reference HLA alleles. HLAProfiler is available at https://expressionanalysis.github.io/HLAProfiler/

    Active Stimuli-Responsive Polymer Surfaces and Thin Films: Design, Properties and Applications: Active Stimuli-Responsive Polymer Surfaces and Thin Films: Design, Properties and Applications

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    Design of 2D and 3D micropatterned materials is highly important for printing technology, microfluidics, microanalytics, information storage, microelectronics and biotechnology. Biotechnology deserves particular interest among the diversity of possible applications because its opens perspectives for regeneration of tissues and organs that can considerably improve our life. In fact, biotechnology is in constant need for development of microstructured materials with controlled architecture. Such materials can serve either as scaffolds or as microanalytical platforms, where cells are able to self-organize in a programmed manner. Microstructured materials, for example, allow in vitro investigation of complex cell-cell interactions, interactions between cells and engineered materials. With the help of patterned surfaces it was demonstrated that cell adhesion and viability as well as differentiation of stem cells1 depend of on the character of nano- and micro- structures 2 as well as their size. There are number of methods based on optical lithography, atomic force microscopy, printing techniques, chemical vapor deposition, which have been developed and successfully applied for 2D patterning. While each of these methods provides particular advantages, a general trade-off between spatial resolution, throughput, “biocompatibility of method” and usability of fabricated patterned surfaces exists. For example, AFM-based techniques allow very high nanometer resolution and can be used to place small numbers of functional proteins with nanometer lateral resolution, but are limited to low writing speeds and small pattern sizes. Albeit, the resolution of photolithography is lower, while it is much faster and cheaper. Therefore, it is highly desirable to develop methods for high-resolution patterning at reasonably low cost and high throughput. Although many approaches to fabricate sophisticated surface patterns exist, they are almost entirely limited to producing fixed patterns that cannot be intentionally modified or switched on the fly in physiologic environment. This limits the usability of a patterned surface to a single specific application and new microstructures have to be fabricated for new applications. Therefore, it is desirable to develop methods for design of switchable and rewritable patterns. Next, the high-energy of the ultraviolet radiation, which is typically used for photolithography, can be harmful for biological species. It is also highly important to develop an approach for photopatterning where visible light is used instead of UV light. Therefore, it is very important for biotechnological applications to achieve good resolution at low costs, create surface with switchable and reconfigurable patterns, perform patterning in mild physiologic conditions and avoid use of harmful UV light. 3D patterning is experimentally more complicated than 2D one and the applicability of available techniques is substantially limited. For example, interference photolithography allows fabrication of 3D structures with limited thickness. Two-photon photolithography, which allows nanoscale resolution, is very slow and highly expensive. Assembling of 3D structures by stacking of 2D ones is time consuming and does not allow fabrication of fine hollow structures. At the same time, nature offers an enormous arsenal of ideas for the design of novel materials with superior properties. In particular, self-assembly and self-organization being the driving principles of structure formation in nature attract significant interest as promising concepts for the design of intelligent materials 3. Self-folding films are the examples of biomimetic materials4. Such films mimic movement mechanisms of plants 5-7 and are able to self-organize and form complex 3D structures. The self-folding films consist of two materials with different properties. At least one of these materials, active one, can change its volume. Because of non-equal expansion of the materials, the self-folding films are able to form a tubes, capsules or more complex structure. Similar to origami, the self-folding films provide unique possibilities for the straightforward fabrication of highly complex 3D micro-structures with patterned inner and outer walls that cannot be achieved using other currently available technologies. The self-folded micro-objects can be assembled into sophisticated, hierarchically-organized 3D super-constructs with structural anisotropy and highly complex surface patterns. Till now most of the research in the field of self-folding films was focused on inorganic materials. Due to their rigidity, limited biocompatibility and non-biodegradability, application of inorganic self-folding materials for biomedical purposes is limited. Polymers are more suitable for these purposes. There are many factors, which make polymer-based self-folding films particularly attractive. There is a variety of polymers sensitive to different stimuli that allows design of self-folding films, which are able to fold in response to various external signals. There are many polymers changing their properties in physiological ranges of pH and temperature as well as polymers sensitive to biochemical processes. There is a variety of biocompatible and biodegradable polymers. These properties make self-folding polymer highly attractive for biological applications. Polymers undergo considerable and reversible changes of volume that allows design of systems with reversible folding. Fabrication of 3D structures with the size ranging from hundreds of nanometers to centimeters is possible. In spite of their attractive properties, the polymer-based systems remained almost out of focus – ca 15 papers including own ones were published on this topic (see own review 8, state October 2011). Thereby the development of biomimetic materials based on self-folding polymer films is highly desired and can open new horizons for the design of unique 3D materials with advanced properties for lab-on-chip applications, smart materials for everyday life and regenerative medicine
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