Kollmar, Martin

[["dc.bibliographiccitation.firstpage","757"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","Bioinformatics"],["dc.bibliographiccitation.lastpage","763"],["dc.bibliographiccitation.volume","27"],["dc.contributor.author","Keller, Oliver"],["dc.contributor.author","Kollmar, Martin"],["dc.contributor.author","Stanke, Mario"],["dc.contributor.author","Waack, Stephan"],["dc.date.accessioned","2018-11-07T08:58:07Z"],["dc.date.available","2018-11-07T08:58:07Z"],["dc.date.issued","2011"],["dc.description.abstract","Mitovation: As improved DNA sequencing techniques have increased enormously the speed of producing new eukaryotic genome assemblies, the further development of automated gene prediction methods continues to be essential. While the classification of proteins into families is a task heavily relying on correct gene predictions, it can at the same time provide a source of additional information for the prediction, complementary to those presently used. Results: We extended the gene prediction software AUGUSTUS by a method that employs block profiles generated from multiple sequence alignments as a protein signature to improve the accuracy of the prediction. Equipped with profiles modelling human dynein heavy chain (DHC) proteins and other families, AUGUSTUS was run on the genomic sequences known to contain members of these families. Compared with AUGUSTUS' ab initio version, the rate of genes predicted with high accuracy showed a dramatic increase."],["dc.description.sponsorship","Deutsche Forschungsgemeinschaft [KO 2251/3-1, KO 2251/6-1, WA 766/6-1]"],["dc.identifier.doi","10.1093/bioinformatics/btr010"],["dc.identifier.isi","000288277300003"],["dc.identifier.pmid","21216780"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/23566"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Oxford Univ Press"],["dc.relation.issn","1460-2059"],["dc.relation.issn","1367-4803"],["dc.title","A novel hybrid gene prediction method employing protein multiple sequence alignments"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Scientific Reports"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Simm, Dominic"],["dc.contributor.author","Popova, Blagovesta"],["dc.contributor.author","Braus, Gerhard H."],["dc.contributor.author","Waack, Stephan"],["dc.contributor.author","Kollmar, Martin"],["dc.date.accessioned","2022-07-01T07:34:51Z"],["dc.date.available","2022-07-01T07:34:51Z"],["dc.date.issued","2022"],["dc.description.abstract","Abstract Heterologous protein expression is an important method for analysing cellular functions of proteins, in genetic circuit engineering and in overexpressing proteins for biopharmaceutical applications and structural biology research. The degeneracy of the genetic code, which enables a single protein to be encoded by a multitude of synonymous gene sequences, plays an important role in regulating protein expression, but substantial uncertainty exists concerning the details of this phenomenon. Here we analyse the influence of a profiled codon usage adaptation approach on protein expression levels in the eukaryotic model organism Saccharomyces cerevisiae . We selected green fluorescent protein (GFP) and human α-synuclein (αSyn) as representatives for stable and intrinsically disordered proteins and representing a benchmark and a challenging test case. A new approach was implemented to design typical genes resembling the codon usage of any subset of endogenous genes. Using this approach, synthetic genes for GFP and αSyn were generated, heterologously expressed and evaluated in yeast. We demonstrate that GFP is expressed at high levels, and that the toxic αSyn can be adapted to endogenous, low-level expression. The new software is publicly available as a web-application for performing host-specific protein adaptations to a set of the most commonly used model organisms ( https://odysseus.motorprotein.de )."],["dc.description.sponsorship"," Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659"],["dc.description.sponsorship"," Georg-August-Universität Göttingen http://dx.doi.org/10.13039/501100003385"],["dc.description.sponsorship","Open-Access-Publikationsfonds 2022"],["dc.identifier.doi","10.1038/s41598-022-13089-1"],["dc.identifier.pii","13089"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/112027"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-581"],["dc.relation.eissn","2045-2322"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Design of typical genes for heterologous gene expression"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","422"],["dc.bibliographiccitation.journal","BMC genomics"],["dc.bibliographiccitation.lastpage","422"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Odronitz, Florian"],["dc.contributor.author","Pillmann, Holger"],["dc.contributor.author","Keller, Oliver"],["dc.contributor.author","Waack, Stephan"],["dc.contributor.author","Kollmar, Martin"],["dc.date.accessioned","2019-07-09T11:40:39Z"],["dc.date.available","2019-07-09T11:40:39Z"],["dc.date.issued","2008"],["dc.description.abstract","BACKGROUND: Obtaining the gene structure for a given protein encoding gene is an important step in many analyses. A software suited for this task should be readily accessible, accurate, easy to handle and should provide the user with a coherent representation of the most probable gene structure. It should be rigorous enough to optimise features on the level of single bases and at the same time flexible enough to allow for cross-species searches. RESULTS: WebScipio, a web interface to the Scipio software, allows a user to obtain the corresponding coding sequence structure of a here given a query protein sequence that belongs to an already assembled eukaryotic genome. The resulting gene structure is presented in various human readable formats like a schematic representation, and a detailed alignment of the query and the target sequence highlighting any discrepancies. WebScipio can also be used to identify and characterise the gene structures of homologs in related organisms. In addition, it offers a web service for integration with other programs. CONCLUSION: WebScipio is a tool that allows users to get a high-quality gene structure prediction from a protein query. It offers more than 250 eukaryotic genomes that can be searched and produces predictions that are close to what can be achieved by manual annotation, for in-species and cross-species searches alike. WebScipio is freely accessible at http://www.webscipio.org."],["dc.identifier.doi","10.1186/1471-2164-9-422"],["dc.identifier.pmid","18801164"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/11177"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/58223"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.issn","1471-2164"],["dc.rights","CC BY 2.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/2.0/"],["dc.subject.mesh","Algorithms"],["dc.subject.mesh","Amino Acid Sequence"],["dc.subject.mesh","Animals"],["dc.subject.mesh","Databases, Genetic"],["dc.subject.mesh","Genomics"],["dc.subject.mesh","Humans"],["dc.subject.mesh","Sequence Alignment"],["dc.subject.mesh","Sequence Analysis, DNA"],["dc.subject.mesh","Sequence Analysis, Protein"],["dc.subject.mesh","Software"],["dc.subject.mesh","Species Specificity"],["dc.subject.mesh","User-Computer Interface"],["dc.title","WebScipio: an online tool for the determination of gene structures using protein sequences."],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","77"],["dc.bibliographiccitation.journal","BMC Bioinformatics"],["dc.bibliographiccitation.volume","14"],["dc.contributor.author","Hammesfahr, Björn"],["dc.contributor.author","Odronitz, Florian"],["dc.contributor.author","Mühlhausen, Stefanie"],["dc.contributor.author","Waack, Stephan"],["dc.contributor.author","Kollmar, Martin"],["dc.date.accessioned","2018-11-07T09:27:09Z"],["dc.date.available","2018-11-07T09:27:09Z"],["dc.date.issued","2013"],["dc.description.abstract","Background: All sequenced eukaryotic genomes have been shown to possess at least a few introns. This includes those unicellular organisms, which were previously suspected to be intron-less. Therefore, gene splicing must have been present at least in the last common ancestor of the eukaryotes. To explain the evolution of introns, basically two mutually exclusive concepts have been developed. The introns-early hypothesis says that already the very first protein-coding genes contained introns while the introns-late concept asserts that eukaryotic genes gained introns only after the emergence of the eukaryotic lineage. A very important aspect in this respect is the conservation of intron positions within homologous genes of different taxa. Results: GenePainter is a standalone application for mapping gene structure information onto protein multiple sequence alignments. Based on the multiple sequence alignments the gene structures are aligned down to single nucleotides. GenePainter accounts for variable lengths in exons and introns, respects split codons at intron junctions and is able to handle sequencing and assembly errors, which are possible reasons for frame-shifts in exons and gaps in genome assemblies. Thus, even gene structures of considerably divergent proteins can properly be compared, as it is needed in phylogenetic analyses. Conserved intron positions can also be mapped to user-provided protein structures. For their visualization GenePainter provides scripts for the molecular graphics system PyMol. Conclusions: GenePainter is a tool to analyse gene structure conservation providing various visualization options. A stable version of GenePainter for all operating systems as well as documentation and example data are available at http://www.motorprotein.de/genepainter.html."],["dc.identifier.doi","10.1186/1471-2105-14-77"],["dc.identifier.isi","000316396200001"],["dc.identifier.pmid","23496949"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/8736"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/30467"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","final"],["dc.notes.submitter","Najko"],["dc.relation.issn","1471-2105"],["dc.relation.orgunit","Fakultät für Mathematik und Informatik"],["dc.rights","CC BY 2.0"],["dc.rights.uri","http://creativecommons.org/licenses/by/2.0"],["dc.title","GenePainter: a fast tool for aligning gene structures of eukaryotic protein families, visualizing the alignments and mapping gene structures onto protein structures"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","265"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","BMC Research Notes"],["dc.bibliographiccitation.volume","4"],["dc.contributor.author","Hatje, Klas"],["dc.contributor.author","Keller, Oliver"],["dc.contributor.author","Hammesfahr, Björn"],["dc.contributor.author","Pillmann, Holger"],["dc.contributor.author","Waack, Stephan"],["dc.contributor.author","Kollmar, Martin"],["dc.date.accessioned","2019-07-09T11:53:04Z"],["dc.date.available","2019-07-09T11:53:04Z"],["dc.date.issued","2011"],["dc.description.abstract","Background Obtaining transcripts of homologs of closely related organisms and retrieving the reconstructed exon-intron patterns of the genes is a very important process during the analysis of the evolution of a protein family and the comparative analysis of the exon-intron structure of a certain gene from different species. Due to the ever-increasing speed of genome sequencing, the gap to genome annotation is growing. Thus, tools for the correct prediction and reconstruction of genes in related organisms become more and more important. The tool Scipio, which can also be used via the graphical interface WebScipio, performs significant hit processing of the output of the Blat program to account for sequencing errors, missing sequence, and fragmented genome assemblies. However, Scipio has so far been limited to high sequence similarity and unable to reconstruct short exons. Results Scipio and WebScipio have fundamentally been extended to better reconstruct very short exons and intron splice sites and to be better suited for cross-species gene structure predictions. The Needleman-Wunsch algorithm has been implemented for the search for short parts of the query sequence that were not recognized by Blat. Those regions might either be short exons, divergent sequence at intron splice sites, or very divergent exons. We have shown the benefit and use of new parameters with several protein examples from completely different protein families in searches against species from several kingdoms of the eukaryotes. The performance of the new Scipio version has been tested in comparison with several similar tools. Conclusions With the new version of Scipio very short exons, terminal and internal, of even just one amino acid can correctly be reconstructed. Scipio is also able to correctly predict almost all genes in cross-species searches even if the ancestors of the species separated more than 100 Myr ago and if the protein sequence identity is below 80%. For our test cases Scipio outperforms all other software tested. WebScipio has been restructured and provides easy access to the genome assemblies of about 640 eukaryotic species. Scipio and WebScipio are freely accessible at http://www.webscipio.org."],["dc.identifier.doi","10.1186/1756-0500-4-265"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/6873"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/60336"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.orgunit","Fakultät für Mathematik und Informatik"],["dc.rights","CC BY 2.0"],["dc.rights.uri","http://creativecommons.org/licenses/by/2.0"],["dc.subject.ddc","510"],["dc.title","Cross-species protein sequence and gene structure prediction with fine-tuned Webscipio 2.0 and Scipio"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.contributor.author","Simm, Dominic"],["dc.contributor.author","Hatje, Klas"],["dc.contributor.author","Waack, Stephan"],["dc.contributor.author","Kollmar, Martin"],["dc.date.accessioned","2019-07-30T10:11:31Z"],["dc.date.available","2019-07-30T10:11:31Z"],["dc.date.issued","2019"],["dc.description.abstract","Coiled-coil regions were among the first protein motifs described structurally and theoretically. The beauty and simplicity of the motif gives hope to detecting coiled-coil regions with reasonable accuracy and precision in any protein sequence. Here, we re-evaluated the most commonly used coiled-coil prediction tools with respect to the most comprehensive reference data set available, the entire Protein Data Base (PDB), down to each amino acid and its secondary structure. Apart from the thirtyfold difference in number of predicted coiled-coils the tools strongly vary in their predictions, across structures and within structures. The evaluation of the false discovery rate and Matthews correlation coefficient, a widely used performance metric for imbalanced data sets, suggests that the tested tools have only limited applicability for large data sets. Coiled-coil predictions strongly impact the functional characterization of proteins, are used for functional genome annotation, and should therefore be supported and validated by additional information."],["dc.identifier.doi","10.1101/675025"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/62191"],["dc.language.iso","en"],["dc.title","Protein function prediction in genomes: Critical assessment of coiled-coil predictions based on protein structure data"],["dc.type","preprint"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","278"],["dc.bibliographiccitation.journal","BMC Bioinformatics"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Keller, Oliver"],["dc.contributor.author","Odronitz, Florian"],["dc.contributor.author","Stanke, Mario"],["dc.contributor.author","Kollmar, Martin"],["dc.contributor.author","Waack, Stephan"],["dc.date.accessioned","2018-11-07T11:14:00Z"],["dc.date.available","2018-11-07T11:14:00Z"],["dc.date.issued","2008"],["dc.description.abstract","Background: For many types of analyses, data about gene structure and locations of non-coding regions of genes are required. Although a vast amount of genomic sequence data is available, precise annotation of genes is lacking behind. Finding the corresponding gene of a given protein sequence by means of conventional tools is error prone, and cannot be completed without manual inspection, which is time consuming and requires considerable experience. Results: Scipio is a tool based on the alignment program BLAT to determine the precise gene structure given a protein sequence and a genome sequence. It identifies intron-exon borders and splice sites and is able to cope with sequencing errors and genes spanning several contigs in genomes that have not yet been assembled to supercontigs or chromosomes. Instead of producing a set of hits with varying confidence, Scipio gives the user a coherent summary of locations on the genome that code for the query protein. The output contains information about discrepancies that may result from sequencing errors. Scipio has also successfully been used to find homologous genes in closely related species. Scipio was tested with 979 protein queries against 16 arthropod genomes ( intra species search). For cross- species annotation, Scipio was used to annotate 40 genes from Homo sapiens in the primates Pongo pygmaeus abelii and Callithrix jacchus. The prediction quality of Scipio was tested in a comparative study against that of BLAT and the well established program Exonerate. Conclusion: Scipio is able to precisely map a protein query onto a genome. Even in cases when there are many sequencing errors, or when incomplete genome assemblies lead to hits that stretch across multiple target sequences, it very often provides the user with the correct determination of intron-exon borders and splice sites, showing an improved prediction accuracy compared to BLAT and Exonerate. Apart from being able to find genes in the genome that encode the query protein, Scipio can also be used to annotate genes in closely related species."],["dc.identifier.doi","10.1186/1471-2105-9-278"],["dc.identifier.isi","000257653900001"],["dc.identifier.pmid","18554390"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/8427"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/54028"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Biomed Central Ltd"],["dc.relation.issn","1471-2105"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Scipio: Using protein sequences to determine the precise exon/intron structures of genes and their orthologs in closely related species"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","12439"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Scientific Reports"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Simm, Dominic"],["dc.contributor.author","Hatje, Klas"],["dc.contributor.author","Waack, Stephan"],["dc.contributor.author","Kollmar, Martin"],["dc.date.accessioned","2021-10-01T09:57:44Z"],["dc.date.available","2021-10-01T09:57:44Z"],["dc.date.issued","2021"],["dc.description.abstract","Abstract Coiled-coil regions were among the first protein motifs described structurally and theoretically. The simplicity of the motif promises that coiled-coil regions can be detected with reasonable accuracy and precision in any protein sequence. Here, we re-evaluated the most commonly used coiled-coil prediction tools with respect to the most comprehensive reference data set available, the entire Protein Data Bank, down to each amino acid and its secondary structure. Apart from the 30-fold difference in minimum and maximum number of coiled coils predicted the tools strongly vary in where they predict coiled-coil regions. Accordingly, there is a high number of false predictions and missed, true coiled-coil regions. The evaluation of the binary classification metrics in comparison with naïve coin-flip models and the calculation of the Matthews correlation coefficient, the most reliable performance metric for imbalanced data sets, suggests that the tested tools’ performance is close to random. This implicates that the tools’ predictions have only limited informative value. Coiled-coil predictions are often used to interpret biochemical data and are part of in-silico functional genome annotation. Our results indicate that these predictions should be treated very cautiously and need to be supported and validated by experimental evidence."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2021"],["dc.identifier.doi","10.1038/s41598-021-91886-w"],["dc.identifier.pii","91886"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/89905"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-469"],["dc.relation.eissn","2045-2322"],["dc.rights","CC BY 4.0"],["dc.title","Critical assessment of coiled-coil predictions based on protein structure data"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]