SERpredict: Detection of tissue- or tumor-specific isoforms generated through exonization of transposable elements

Background: Transposed elements (TEs) are known to affect transcriptomes, because either new exons are generated from intronic transposed elements (this is called exonization), or the element inserts into the exon, leading to a new transcript. Several examples in the literature show that isoforms generated by an exonization are specific to a certain tissue (for example the heart muscle) or inflict a disease. Thus, exonizations can have negative effects for the transcriptome of an organism. Results: As we aimed at detecting other tissue- or tumor-specific isoforms in human and mouse genomes which were generated through exonization of a transposed element, we designed the automated analysis pipeline SERpredict (SER = Specific Exonized Retroelement) making use of Bayesian Statistics. With this pipeline, we found several genes in which a transposed element formed a tissue- or tumor-specific isoform. Conclusion: Our results show that SERpredict produces relevant results, demonstrating the importance of transposed elements in shaping both the human and the mouse transcriptomes. The effect of transposed elements on the human transcriptome is several times higher than the effect on the mouse transcriptome, due to the contribution of the primate-specific Alu element

Second-order electronic correlation effects in a one-dimensional metal

The Pariser-Parr-Pople (PPP) model of a single-band one-dimensional (1D) metal is studied at the Hartree-Fock level, and by using the second-order perturbation theory of the electronic correlation. The PPP model provides an extension of the Hubbard model by properly accounting for the long-range character of the electron-electron repulsion. Both finite and infinite version of the 1D-metal model are considered within the PPP and Hubbard approximations. Calculated are the second-order electronic-correlation corrections to the total energy, and to the electronic-energy bands. Our results for the PPP model of 1D metal show qualitative similarity to the coupled-cluster results for the 3D electron-gas model. The picture of the 1D-metal model that emerges from the present study provides a support for the hypothesis that the normal metallic state of the 1D metal is different from the ground state.Comment: 21 pages, 16 figures; v2: small correction in title, added 3 references, extended and reformulated a few paragraphs (detailed information at the end of .tex file); added color to figure

A Wannier-function-based ab initio Hartree-Fock study of polyethylene

In the present letter, we report the extension of our Wannier-function-based ab initio Hartree-Fock approach---meant originally for three-dimensional crystalline insulators---to deal with quasi-one-dimensional periodic systems such as polymers. The system studied is all-transoid polyethylene, and results on optimized lattice parameters, cohesive energy and the band structure utilizing 6-31G** basis sets are presented. Our results are also shown to be in excellent agreement with those obtained with traditional Bloch-orbital-based approaches.Comment: 15 Pages, RevTex, inludes four figures, Chem. Phys. Letts., in press (1998

cDNA2Genome: A tool for mapping and annotating cDNAs

BACKGROUND: In the last years several high-throughput cDNA sequencing projects have been funded worldwide with the aim of identifying and characterizing the structure of complete novel human transcripts. However some of these cDNAs are error prone due to frameshifts and stop codon errors caused by low sequence quality, or to cloning of truncated inserts, among other reasons. Therefore, accurate CDS prediction from these sequences first require the identification of potentially problematic cDNAs in order to speed up the posterior annotation process. RESULTS: cDNA2Genome is an application for the automatic high-throughput mapping and characterization of cDNAs. It utilizes current annotation data and the most up to date databases, especially in the case of ESTs and mRNAs in conjunction with a vast number of approaches to gene prediction in order to perform a comprehensive assessment of the cDNA exon-intron structure. The final result of cDNA2Genome is an XML file containing all relevant information obtained in the process. This XML output can easily be used for further analysis such us program pipelines, or the integration of results into databases. The web interface to cDNA2Genome also presents this data in HTML, where the annotation is additionally shown in a graphical form. cDNA2Genome has been implemented under the W3H task framework which allows the combination of bioinformatics tools in tailor-made analysis task flows as well as the sequential or parallel computation of many sequences for large-scale analysis. CONCLUSIONS: cDNA2Genome represents a new versatile and easily extensible approach to the automated mapping and annotation of human cDNAs. The underlying approach allows sequential or parallel computation of sequences for high-throughput analysis of cDNAs

The structure and energetics of 3^3He and 4^4He nanodroplets doped with alkaline earth atoms

We present systematic results, based on density functional calculations, for the structure and energetics of $^3$He and $^4$He nanodroplets doped with alkaline earth atoms. We predict that alkaline earth atoms from Mg to Ba go to the center of $^3$He drops, whereas Ca, Sr, and Ba reside in a deep dimple at the surface of $^4$He drops, and Mg is at their center. For Ca and Sr, the structure of the dimples is shown to be very sensitive to the He-alkaline earth pair potentials used in the calculations. The $5s5p\leftarrow5s^2$ transition of strontium atoms attached to helium nanodroplets of either isotope has been probed in absorption experiments. The spectra show that strontium is solvated inside $^3$He nanodroplets, supporting the calculations. In the light of our findings, we emphasize the relevance of the heavier alkaline earth atoms for analyzing mixed $^3$He-$^4$He nanodroplets, and in particular, we suggest their use to experimentally probe the $^3$He-$^4$He interface.Comment: Typeset using Revtex, 20 pages and 8 Postscript file

DoOPSearch: a web-based tool for finding and analysing common conserved motifs in the promoter regions of different chordate and plant genes

BACKGROUND: The comparative genomic analysis of a large number of orthologous promoter regions of the chordate and plant genes from the DoOP databases shows thousands of conserved motifs. Most of these motifs differ from any known transcription factor binding site (TFBS). To identify common conserved motifs, we need a specific tool to be able to search amongst them. Since conserved motifs from the DoOP databases are linked to genes, the result of such a search can give a list of genes that are potentially regulated by the same transcription factor(s). RESULTS: We have developed a new tool called DoOPSearch for the analysis of the conserved motifs in the promoter regions of chordate or plant genes. We used the orthologous promoters of the DoOP database to extract thousands of conserved motifs from different taxonomic groups. The advantage of this approach is that different sets of conserved motifs might be found depending on how broad the taxonomic coverage of the underlying orthologous promoter sequence collection is (consider e.g. primates vs. mammals or Brassicaceae vs. Viridiplantae). The DoOPSearch tool allows the users to search these motif collections or the promoter regions of DoOP with user supplied query sequences or any of the conserved motifs from the DoOP database. To find overrepresented gene ontologies, the gene lists obtained can be analysed further using a modified version of the GeneMerge program. CONCLUSION: We present here a comparative genomics based promoter analysis tool. Our system is based on a unique collection of conserved promoter motifs characteristic of different taxonomic groups. We offer both a command line and a web-based tool for searching in these motif collections using user specified queries. These can be either short promoter sequences or consensus sequences of known transcription factor binding sites. The GeneMerge analysis of the search results allows the user to identify statistically overrepresented Gene Ontology terms that might provide a clue on the function of the motifs and genes

Dynamical generalization of a solvable family of two-electron model atoms with general interparticle repulsion

Holas, Howard and March [Phys. Lett. A {\bf 310}, 451 (2003)] have obtained analytic solutions for ground-state properties of a whole family of two-electron spin-compensated harmonically confined model atoms whose different members are characterized by a specific interparticle potential energy u($r_{12}$). Here, we make a start on the dynamic generalization of the harmonic external potential, the motivation being the serious criticism levelled recently against the foundations of time-dependent density-functional theory (e.g. [J. Schirmer and A. Dreuw, Phys. Rev. A {\bf 75}, 022513 (2007)]). In this context, we derive a simplified expression for the time-dependent electron density for arbitrary interparticle interaction, which is fully determined by an one-dimensional non-interacting Hamiltonian. Moreover, a closed solution for the momentum space density in the Moshinsky model is obtained.Comment: 5 pages, submitted to J. Phys.

Automatic detection of exonic splicing enhancers (ESEs) using SVMs

<p>Abstract</p> <p>Background</p> <p>Exonic splicing enhancers (ESEs) activate nearby splice sites and promote the inclusion (vs. exclusion) of exons in which they reside, while being a binding site for SR proteins. To study the impact of ESEs on alternative splicing it would be useful to have a possibility to detect them in exons. Identifying SR protein-binding sites in human DNA sequences by machine learning techniques is a formidable task, since the exon sequences are also constrained by their functional role in coding for proteins.</p> <p>Results</p> <p>The choice of training examples needed for machine learning approaches is difficult since there are only few exact locations of human ESEs described in the literature which could be considered as positive examples. Additionally, it is unclear which sequences are suitable as negative examples. Therefore, we developed a motif-oriented data-extraction method that extracts exon sequences around experimentally or theoretically determined ESE patterns. Positive examples are restricted by heuristics based on known properties of ESEs, e.g. location in the vicinity of a splice site, whereas negative examples are taken in the same way from the middle of long exons. We show that a suitably chosen SVM using optimized sequence kernels (e.g., combined oligo kernel) can extract meaningful properties from these training examples. Once the classifier is trained, every potential ESE sequence can be passed to the SVM for verification. Using SVMs with the combined oligo kernel yields a high accuracy of about 90 percent and well interpretable parameters.</p> <p>Conclusion</p> <p>The motif-oriented data-extraction method seems to produce consistent training and test data leading to good classification rates and thus allows verification of potential ESE motifs. The best results were obtained using an SVM with the combined oligo kernel, while oligo kernels with oligomers of a certain length could be used to extract relevant features.</p