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Biomedical subjects

Martti T Tammi

Publications and source records attributed to Martti T Tammi.

8 recordsLinked to original sources

AllerTool: a web server for predicting allergenicity and allergic cross-reactivity in proteins.

UNLABELLED: Assessment of potential allergenicity and patterns of cross-reactivity is necessary whenever novel proteins are introduced into human food chain. Current bioinformatic methods in allergology focus mainly on the prediction of allergenic proteins, with no information on cross-reactivity patterns among known allergens. In this study, we present AllerTool, a web server with essential tools for the assessment of predicted as well as published cross-reactivity patterns of allergens. The analysis tools include graphical representation of allergen cross-reactivity information; a local sequence comparison tool that displays information of known cross-reactive allergens; a sequence similarity search tool for assessment of cross-reactivity in accordance to FAO/WHO Codex alimentarius guidelines; and a method based on support vector machine (SVM). A 10-fold cross-validation results showed that the area under the receiver operating curve (A(ROC)) of SVM models is 0.90 with 86.00% sensitivity (SE) at specificity (SP) of 86.00%. AVAILABILITY: AllerTool is freely available at http://research.i2r.a-star.edu.sg/AllerTool/.

Algorithms↗

DNPTrapper: an assembly editing tool for finishing and analysis of complex repeat regions.

BACKGROUND: Many genome projects are left unfinished due to complex, repeated regions. Finishing is the most time consuming step in sequencing and current finishing tools are not designed with particular attention to the repeat problem. RESULTS: We have developed DNPTrapper, a shotgun sequence finishing tool, specifically designed to address the problems posed by the presence of repeated regions in the target sequence. The program detects and visualizes single base differences between nearly identical repeat copies, and offers the overview and flexibility needed to rapidly resolve complex regions within a working session. The use of a database allows large amounts of data to be stored and handled, and allows viewing of mammalian size genomes. The program is available under an Open Source license. CONCLUSION: With DNPTrapper, it is possible to separate repeated regions that previously were considered impossible to resolve, and finishing tasks that previously took days or weeks can be resolved within hours or even minutes.

Algorithms↗

Cloning of a human parvovirus by molecular screening of respiratory tract samples.

The identification of new virus species is a key issue for the study of infectious disease but is technically very difficult. We developed a system for large-scale molecular virus screening of clinical samples based on host DNA depletion, random PCR amplification, large-scale sequencing, and bioinformatics. The technology was applied to pooled human respiratory tract samples. The first experiments detected seven human virus species without the use of any specific reagent. Among the detected viruses were one coronavirus and one parvovirus, both of which were at that time uncharacterized. The parvovirus, provisionally named human bocavirus, was in a retrospective clinical study detected in 17 additional patients and associated with lower respiratory tract infections in children. The molecular virus screening procedure provides a general culture-independent solution to the problem of detecting unknown virus species in single or pooled samples. We suggest that a systematic exploration of the viruses that infect humans, "the human virome," can be initiated.

Child, Preschool↗

The genome sequence of Trypanosoma cruzi, etiologic agent of Chagas disease.

Whole-genome sequencing of the protozoan pathogen Trypanosoma cruzi revealed that the diploid genome contains a predicted 22,570 proteins encoded by genes, of which 12,570 represent allelic pairs. Over 50% of the genome consists of repeated sequences, such as retrotransposons and genes for large families of surface molecules, which include trans-sialidases, mucins, gp63s, and a large novel family (>1300 copies) of mucin-associated surface protein (MASP) genes. Analyses of the T. cruzi, T. brucei, and Leishmania major (Tritryp) genomes imply differences from other eukaryotes in DNA repair and initiation of replication and reflect their unusual mitochondrial DNA. Although the Tritryp lack several classes of signaling molecules, their kinomes contain a large and diverse set of protein kinases and phosphatases; their size and diversity imply previously unknown interactions and regulatory processes, which may be targets for intervention.

Animals↗

ReDiT: Repeat Discrepancy Tagger--a shotgun assembly finishing aid.

UNLABELLED: Finishing, i.e. gap closure and editing, is the most time-consuming part of genome sequencing. Repeated sequences together with sequencing errors complicate the assembly and often result in misassemblies that are difficult to correct. Repeat Discrepancy Tagger (ReDiT) is a tool designed to aid in the finishing step. This software processes assembly results produced by any fragment assembly program that outputs ace files. The input sequences are analyzed to determine possible differences between repeated sequences. The output is written as tags in an ace file that can be viewed by, e.g. the Consed sequence editor. AVAILABILITY: The ReDiT program is freely available at http://web.cgb.ki.se/redit

Algorithms↗

Correcting errors in shotgun sequences.

Sequencing errors in combination with repeated regions cause major problems in shotgun sequencing, mainly due to the failure of assembly programs to distinguish single base differences between repeat copies from erroneous base calls. In this paper, a new strategy designed to correct errors in shotgun sequence data using defined nucleotide positions, DNPs, is presented. The method distinguishes single base differences from sequencing errors by analyzing multiple alignments consisting of a read and all its overlaps with other reads. The construction of multiple alignments is performed using a novel pattern matching algorithm, which takes advantage of the symmetry between indices that can be computed for similar words of the same length. This allows for rapid construction of multiple alignments, with no previous pair-wise matching of sequence reads required. Results from a C++ implementation of this method show that up to 99% of sequencing errors can be corrected, while up to 87% of the single base differences remain and up to 80% of the corrected reads contain at most one error. The results also show that the method outperforms the error correction method used in the EULER assembler. The prototype software, MisEd, is freely available from the authors for academic use.

Algorithms↗

TRAP: Tandem Repeat Assembly Program produces improved shotgun assemblies of repetitive sequences.

The software commonly used for assembly of shotgun sequence data has several limitations. One such limitation becomes obvious when repetitive sequences are encountered. Shotgun assembly is a difficult task, even for non-repetitive regions, but the use of quality assessments of the data and efficient matching algorithms have made it possible to assemble most sequences efficiently. In the case of highly repetitive sequences, however, these algorithms fail to distinguish between sequencing errors and single base differences in regions containing nearly identical repeats. None of the currently available fragment assembly programs are able to correctly assemble highly similar repetitive data, and we, therefore, present a novel shotgun assembly program, Tandem Repeat Assembly Program (TRAP). The main feature of this program is the ability to separate long repetitive regions from each other by distinguishing single base substitutions as well as insertions/deletions from sequencing errors. This is accomplished by using a novel multiple-alignment based analysis method. Since repeats are a common complication in most sequencing projects, this software should be of use for the whole sequencing community.

Algorithms↗

Separation of nearly identical repeats in shotgun assemblies using defined nucleotide positions, DNPs.

An increasingly important problem in genome sequencing is the failure of the commonly used shotgun assembly programs to correctly assemble repetitive sequences. The assembly of non-repetitive regions or regions containing repeats considerably shorter than the average read length is in practice easy to solve, while longer repeats have been a difficult problem. We here present a statistical method to separate arbitrarily long, almost identical repeats, which makes it possible to correctly assemble complex repetitive sequence regions. The differences between repeat units may be as low as 1% and the sequencing error may be up to ten times higher. The method is based on the realization that a comparison of only a part of all overlapping sequences at a time in a data set does not generate enough information for a conclusive analysis. Our method uses optimal multi-alignments consisting of all the overlaps of each read. This makes it possible to determine defined nucleotide positions, DNPs, which constitute the differences between the repeat units. Differences between repeats are distinguished from sequencing errors using statistical methods, where the probabilities of obtaining certain combinations of candidate DNPs are calculated using the information from the multi-alignments. The use of DNPs and combinations of DNPs will allow for optimal and rapid assemblies of repeated regions. This method can solve repeats that differ in only two positions in a read length, which is the theoretical limit for repeat separation. We predict that this method will be highly useful in shotgun sequencing in the future.

Algorithms↗