PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7645
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Editorial Citation - WoS: 2Computational Mirnomics - Integrative Approaches(Informationsmanagement in der Biotechnologie e.V. (IMBio e.V.), 2017) Hofestaedt, Ralf; Schreiber, Falk; Sommer, Bjoern; Allmer, JensWith this special issue on Computational miRNomics, we would like to start a new generation of publications in the Journal of Integrative Bioinformatics (JIB). From 2017 onwards, JIB will be published by De Gruyter which is one of the largest Open Access publishers in Germany with a long history. Established in 1918 with roots reaching even further back, the JIB editorial board decided that De Gruyter is the perfect partner to increase the level of professionalism for our publication processing and journal development.Article Citation - WoS: 4Citation - Scopus: 9Pgminer Reloaded, Fully Automated Proteogenomic Annotation Tool Linking Genomes To Proteomes(Informationsmanagement in der Biotechnologie e.V. (IMBio e.V.), 2016) Has, Canan; Lashin, Sergey A.; Kochetov, Alexey; Allmer, JensImprovements in genome sequencing technology increased the availability of full genomes and transcriptomes of many organisms. However, the major benefit of massive parallel sequencing is to better understand the organization and function of genes which then lead to understanding of phenotypes. In order to interpret genomic data with automated gene annotation studies, several tools are currently available. Even though the accuracy of computational gene annotation is increasing, a combination of multiple lines of experimental evidences should be gathered. Mass spectrometry allows the identification and sequencing of proteins as major gene products; and it is only these proteins that conclusively show whether a part of a genome is a coding region or not to result in phenotypes. Therefore, in the field of proteogenomics, the validation of computational methods is done by exploiting mass spectrometric data. As a result, identification of novel protein coding regions, validation of current gene models, and determination of upstream and downstream regions of genes can be achieved. In this paper, we present new functionality for our proteogenomic tool, PGMiner which performs all proteogenomic steps like acquisition of mass spectrometric data, peptide identification against preprocessed sequence databases, assignment of statistical confidence to identified peptides, mapping confident peptides to gene models, and result visualization. The extensions cover determining proteotypic peptides and thus unambiguous protein identification. Furthermore, peptides conflicting with gene models can now automatically assessed within the context of predicted alternative open reading frames.Article Citation - WoS: 7Citation - Scopus: 5A Machine Learning Approach for Microrna Precursor Prediction in Retro-Transcribing Virus Genomes(Informationsmanagement in der Biotechnologie e.V. (IMBio e.V.), 2016) Saçar Demirci, Müşerref Duygu; Toprak, Mustafa; Allmer, JensIdentification of microRNA (miRNA) precursors has seen increased efforts in recent years. The difficulty in experimental detection of pre-miRNAs increased the usage of computational approaches. Most of these approaches rely on machine learning especially classification. In order to achieve successful classification, many parameters need to be considered such as data quality, choice of classifier settings, and feature selection. For the latter one, we developed a distributed genetic algorithm on HTCondor to perform feature selection. Moreover, we employed two widely used classification algorithms libSVM and random forest with different settings to analyze the influence on the overall classification performance. In this study we analyzed 5 human retro virus genomes; Human endogenous retrovirus K113, Hepatitis B virus (strain ayw), Human T lymphotropic virus 1, Human T lymphotropic virus 2, Human immunodeficiency virus 2, and Human immunodeficiency virus 1. We then predicted pre-miRNAs by using the information from known virus and human pre-miRNAs. Our results indicate that these viruses produce novel unknown miRNA precursors which warrant further experimental validation.Article Citation - WoS: 14Visualization and Analysis of Micrornas Within Kegg Pathways Using Vanesa(Walter de Gruyter GmbH, 2017) Hamzeiy, Hamid; Suluyayla, Rabia; Brinkrolf, Christoph; Janowski, Sebastian Jan; Hofestaedt, Ralf; Allmer, JensMicroRNAs (miRNAs) are small RNA molecules which are known to take part in post-transcriptional regulation of gene expression. Here, VANESA, an existing platform for reconstructing, visualizing, and analysis of large biological networks, has been further expanded to include all experimentally validated human miRNAs available within miRBase, TarBase and miRTarBase. This is done by integrating a custom hybrid miRNA database to DAWIS-M.D., VANESA's main data source, enabling the visualization and analysis of miRNAs within large biological pathways such as those found within the Kyoto Encyclopedia of Genes and Genomes (KEGG). Interestingly, 99.15 % of human KEGG pathways either contain genes which are targeted by miRNAs or harbor them. This is mainly due to the high number of interaction partners that each miRNA could have (e.g.: hsa-miR-335-5p targets 2544 genes and 71 miRNAs target NUFIP2). We demonstrate the usability of our system by analyzing the measles virus KEGG pathway as a proof-of-principle model and further highlight the importance of integrating miRNAs (both experimentally validated and predicted) into biological networks for the elucidation of novel miRNA-mRNA interactions of biological importance.Article Citation - WoS: 4Citation - Scopus: 4Improving the Quality of Positive Datasets for the Establishment of Machine Learning Models for Pre-Microrna Detection(Informationsmanagement in der Biotechnologie e.V. (IMBio e.V.), 2017) Saçar Demirci, Müşerref Duygu; Allmer, JensMicroRNAs (miRNAs) are involved in the post-transcriptional regulation of protein abundance and thus have a great impact on the resulting phenotype. It is, therefore, no wonder that they have been implicated in many diseases ranging from virus infections to cancer. This impact on the phenotype leads to a great interest in establishing the miRNAs of an organism. Experimental methods are complicated which led to the development of computational methods for pre-miRNA detection. Such methods generally employ machine learning to establish models for the discrimination between miRNAs and other sequences. Positive training data for model establishment, for the most part, stems from miRBase, the miRNA registry. The quality of the entries in miRBase has been questioned, though. This unknown quality led to the development of filtering strategies in attempts to produce high quality positive datasets which can lead to a scarcity of positive data. To analyze the quality of filtered data we developed a machine learning model and found it is well able to establish data quality based on intrinsic measures. Additionally, we analyzed which features describing pre-miRNAs could discriminate between low and high quality data. Both models are applicable to data from miRBase and can be used for establishing high quality positive data. This will facilitate the development of better miRNA detection tools which will make the prediction of miRNAs in disease states more accurate. Finally, we applied both models to all miRBase data and provide the list of high quality hairpins.Article Citation - WoS: 7Altorfev Facilitates the Prediction of Alternative Open Reading Frames in Eukaryotic Mrnas(Oxford University Press, 2017) Kochetov, Alex V.; Allmer, Jens; Klimenko, Alexandra I.; Zuraev, Bulat S.; Matushkin, Yury G.; Lashin, Sergey A.Motivation: Protein synthesis is not a straight forward process and one gene locus can produce many isoforms, for example, by starting mRNA translation from alternative start sites. altORF evaluator (altORFev) predicts alternative open reading frames within eukaryotic mRNA translated by a linear scanning mechanism and its modifications (leaky scanning and reinitiation). The program reveals the efficiently translated altORFs recognized by the majority of 40S ribosomal subunits landing on the 50-end of an mRNA. This information aids to reveal the functions of eukaryotic genes connected to synthesis of either unknown isoforms of annotated proteins or new unrelated polypeptides.Article Citation - WoS: 14Citation - Scopus: 16Transcriptomic Analysis of Boron Hyperaccumulation Mechanisms in Puccinellia Distans(Elsevier Ltd., 2018) Öztürk, Saniye Elvan; Göktay, Mehmet; Has, Canan; Babaoğlu, Mehmet; Allmer, Jens; Doğanlar, Sami; Frary, AnnePuccinellia distans, common alkali grass, is found throughout the world and can survive in soils with boron concentrations that are lethal for other plant species. Indeed, P. distans accumulates very high levels of this element. Despite these interesting features, very little research has been performed to elucidate the boron tolerance mechanism in this species. In this study, P. distans samples were treated for three weeks with normal (0.5 mg L−1) and elevated (500 mg L−1) boron levels in hydroponic solution. Expressed sequence tags (ESTs) derived from shoot tissue were analyzed by RNA sequencing to identify genes up and down-regulated under boron stress. In this way, 3312 differentially expressed transcripts were detected, 67.7% of which were up-regulated and 32.3% of which were down-regulated in boron-treated plants. To partially confirm the RNA sequencing results, 32 randomly selected transcripts were analyzed for their expression levels in boron-treated plants. The results agreed with the expected direction of change (up or down-regulation). A total of 1652 transcripts had homologs in A. thaliana and/or O. sativa and mapped to 1107 different proteins. Functional annotation of these proteins indicated that the boron tolerance and hyperaccumulation mechanisms of P. distans involve many transcriptomic changes including: alterations in the malate pathway, changes in cell wall components that may allow sequestration of excess boron without toxic effects, and increased expression of at least one putative boron transporter and two putative aquaporins. Elucidation of the boron accumulation mechanism is important in developing approaches for bioremediation of boron contaminated soils.Article Citation - WoS: 11Citation - Scopus: 11The Expressed Microrna-Mrna Interactions of Toxoplasma Gondii(Frontiers Media S.A., 2018) Acar, İlhan Erkin; Saçar Demirci, Müşerref Duygu; Groß, Uwe; Allmer, JensMicroRNAs (miRNAs) are involved in post-transcriptional modulation of gene expression and thereby have a large influence on the resulting phenotype. We have previously shown that miRNAs may be involved in the communication between Toxoplasma gondii and its hosts and further confirmed a number of proposed specific miRNAs. Yet, little is known about the internal regulation via miRNAs in T. gondii. Therefore, we predicted pre-miRNAs directly from the type II ME49 genome and filtered them. For the confident hairpins, we predicted the location of the mature miRNAs and established their target genes. To add further confidence, we evaluated whether the hairpins and their targets were co-expressed. Such co-expressed miRNA and target pairs define a functional interaction. We extracted all such functional interactions and analyzed their differential expression among strains of all three clonal lineages (RH, PLK, and CTG) and between the two stages present in the intermediate host (tachyzoites and bradyzoites). Overall, we found ~65,000 expressed interactions of which ~5,500 are differentially expressed among strains but none are significantly differentially expressed between developmental stages. Since miRNAs and target decoys can be used as therapeutics we believe that the list of interactions we provide will lead to novel approaches in the treatment of toxoplasmosis.Article Citation - WoS: 37Citation - Scopus: 45On the Performance of Pre-Microrna Detection Algorithms(Nature Publishing Group, 2017) Saçar Demirci, Müşerref Duygu; Baumbach, Jan; Allmer, JensMicroRNAs are crucial for post-transcriptional gene regulation, and their dysregulation has been associated with diseases like cancer and, therefore, their analysis has become popular. The experimental discovery of miRNAs is cumbersome and, thus, many computational tools have been proposed. Here we assess 13 ab initio pre-miRNA detection approaches using all relevant, published, and novel data sets while judging algorithm performance based on ten intrinsic performance measures. We present an extensible framework, izMiR, which allows for the unbiased comparison of existing algorithms, adding new ones, and combining multiple approaches into ensemble methods. In an exhaustive attempt, we condense the results of millions of computations and show that no method is clearly superior; however, we provide a guideline for biomedical researchers to select a tool. Finally, we demonstrate that combining all of the methods into one ensemble approach, for the first time, allows reliable purely computational pre-miRNA detection in large eukaryotic genomes.Article Citation - WoS: 19Citation - Scopus: 29One Step Forward, Two Steps Back; Xeno-Micrornas Reported in Breast Milk Are Artifacts(Public Library of Science, 2016) Bağcı, Caner; Allmer, JensBackground: MicroRNAs (miRNAs) are short RNA sequences that guide post-transcriptional regulation of gene expression via complementarity to their target mRNAs. Discovered only recently, miRNAs have drawn a lot of attention. Multiple protein complexes interact to first cleave a hairpin from nascent RNA, export it into the cytosol, trim its loop, and incorporate it into the RISC complex which is important for binding its target mRNA. This process works within one cell, but circulating miRNAs have been described suggesting a role in cell-cell communication. Motivation: Viruses and intracellular parasites like Toxoplasma gondii use miRNAs to manipulate host gene expression from within the cellular environment. However, recent research has claimed that a rice miRNA may regulate human gene expression. Despite ongoing debates about these findings and general reluctance to accept them, a recent report claimed that foodborne plant miRNAs pass through the digestive tract, travel through blood to be incorporated by alveolar cells excreting milk. The miRNAs are then said to have some immunerelated function in the newborn. Principal Findings: We acquired the data that supports their claim and performed further analyses. In addition to the reported miRNAs, we were able to detect almost complete mRNAs and found that the foreign RNA expression profiles among samples are exceedingly similar. Inspecting the source of the data helped understand how RNAs could contaminate the samples. Conclusion: Viewing these findings in context with the difficulties foreign RNAs face on their route into breast milk and the fact that many identified foodborne miRNAs are not from actual food sources, we can conclude beyond reasonable doubt that the original claims and evidence presented may be due to artifacts. We report that the study claiming their existence is more likely to have detected RNA contamination than miRNAs.