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- Andersson, Claes R., et al.
(författare)
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Bayesian detection of periodic mRNA time profiles withouth use of training examples
- 2006
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 7, s. 63-
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Detection of periodically expressed genes from microarray data without use of known periodic and non-periodic training examples is an important problem, e.g. for identifying genes regulated by the cell-cycle in poorly characterised organisms. Commonly the investigator is only interested in genes expressed at a particular frequency that characterizes the process under study but this frequency is seldom exactly known. Previously proposed detector designs require access to labelled training examples and do not allow systematic incorporation of diffuse prior knowledge available about the period time. RESULTS: A learning-free Bayesian detector that does not rely on labelled training examples and allows incorporation of prior knowledge about the period time is introduced. It is shown to outperform two recently proposed alternative learning-free detectors on simulated data generated with models that are different from the one used for detector design. Results from applying the detector to mRNA expression time profiles from S. cerevisiae showsthat the genes detected as periodically expressed only contain a small fraction of the cell-cycle genes inferred from mutant phenotype. For example, when the probability of false alarm was equal to 7%, only 12% of the cell-cycle genes were detected. The genes detected as periodically expressed were found to have a statistically significant overrepresentation of known cell-cycle regulated sequence motifs. One known sequence motif and 18 putative motifs, previously not associated with periodic expression, were also over represented. CONCLUSION: In comparison with recently proposed alternative learning-free detectors for periodic gene expression, Bayesian inference allows systematic incorporation of diffuse a priori knowledge about, e.g. the period time. This results in relative performance improvements due to increased robustness against errors in the underlying assumptions. Results from applying the detector to mRNA expression time profiles from S. cerevisiae include several new findings that deserve further experimental studies.
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| 2. |
- Andersson, Claes R., et al.
(författare)
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In vitro drug sensitivity-gene expression correlations involve a tissue of origin dependency
- 2007
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Ingår i: Journal of chemical information and modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 47:1, s. 239-248
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Tidskriftsartikel (refereegranskat)abstract
- A major concern of chemogenomics is to associate drug activity with biological variables. Several reports have clustered cell line drug activity profiles as well as drug activity-gene expression correlation profiles and noted that the resulting groupings differ but still reflect mechanism of action. The present paper shows that these discrepancies can be viewed as a weighting of drug-drug distances, the weights depending on which cell lines the two drugs differ in.
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| 3. |
- Andersson, Claes R., et al.
(författare)
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Revealing cell cycle control by combining model-based detection of periodic expression with novel cis-regulatory descriptors
- 2007
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Ingår i: BMC Systems Biology. - : Springer Science and Business Media LLC. - 1752-0509. ; 1, s. 45-
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Tidskriftsartikel (refereegranskat)abstract
- Background: We address the issue of explaining the presence or absence of phase-specific transcription in budding yeast cultures under different conditions. To this end we use a model-based detector of gene expression periodicity to divide genes into classes depending on their behavior in experiments using different synchronization methods. While computational inference of gene regulatory circuits typically relies on expression similarity (clustering) in order to find classes of potentially co-regulated genes, this method instead takes advantage of known time profile signatures related to the studied process. Results: We explain the regulatory mechanisms of the inferred periodic classes with cis-regulatory descriptors that combine upstream sequence motifs with experimentally determined binding of transcription factors. By systematic statistical analysis we show that periodic classes are best explained by combinations of descriptors rather than single descriptors, and that different combinations correspond to periodic expression in different classes. We also find evidence for additive regulation in that the combinations of cis-regulatory descriptors associated with genes periodically expressed in fewer conditions are frequently subsets of combinations associated with genes periodically expression in more conditions. Finally, we demonstrate that our approach retrieves combinations that are more specific towards known cell-cycle related regulators than the frequently used clustering approach. Conclusion: The results illustrate how a model-based approach to expression analysis may be particularly well suited to detect biologically relevant mechanisms. Our new approach makes it possible to provide more refined hypotheses about regulatory mechanisms of the cell cycle and it can easily be adjusted to reveal regulation of other, non-periodic, cellular processes.
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| 6. |
- Englund, Markus, et al.
(författare)
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Phylogenetic relationships and generic delimitation in Inuleae subtribe Inulinae (Asteraceae) based on ITS and cpDNA sequence data
- 2009
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Ingår i: Cladistics. - : Wiley. - 0748-3007 .- 1096-0031. ; 25:4, s. 319-352
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Tidskriftsartikel (refereegranskat)abstract
- Phylogenetic relationships in Inuleae subtribe Inulinae (Asteraceae) were investigated. DNA sequence data from three chloroplast regions (ndhF,trnL–F and psbA–trnH) and the nuclear ribosomal internal transcribed spacer (ITS) region were analysed separately and in combination using parsimony and Bayesian inference. A total of 163 ingroup taxa were included, of which 60 were sampled for all four markers. Conflicts between chloroplast and nuclear data were assessed using partitioned Bremer support (PBS). Rather than averaging PBS over several trees from constrained searches, individual trees were considered by evaluating PBS ranges. Criteria to be used in the detection of a significant conflict between data partitions are proposed. Three nodes in the total data tree were found to encompass significant conflict that could result from ancient hybridization. Neither of the large, heterogeneous and widespread genera Inula and Pulicaria is monophyletic. A monophyletic group ("the Inula complex") that comprises all species of Inula include also Telekia, Carpesium, Chrysophthalmum, Rhanteriopsis, Amblyocarpum, and Pentanema sensu stricto. Two species of Pentanema were found to be closer to Blumea (including Blumeopsis and Merrittia) and Caesulia. The monophyletic "Pulicaria complex" includes all taxa with heteromorphic pappus. Within this group, Francoeuria is distinct from Pulicaria and merits recognition as a separate genus.
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| 7. |
- Freyhult, Eva, et al.
(författare)
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Unbiased descriptor and parameter selection confirms the potential of proteochemometric modelling
- 2005
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 6, s. 50-
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Tidskriftsartikel (refereegranskat)abstract
- Background Proteochemometrics is a new methodology that allows prediction of protein function directly from real interaction measurement data without the need of 3D structure information. Several reported proteochemometric models of ligand-receptor interactions have already yielded significant insights into various forms of bio-molecular interactions. The proteochemometric models are multivariate regression models that predict binding affinity for a particular combination of features of the ligand and protein. Although proteochemometric models have already offered interesting results in various studies, no detailed statistical evaluation of their average predictive power has been performed. In particular, variable subset selection performed to date has always relied on using all available examples, a situation also encountered in microarray gene expression data analysis. Results A methodology for an unbiased evaluation of the predictive power of proteochemometric models was implemented and results from applying it to two of the largest proteochemometric data sets yet reported are presented. A double cross-validation loop procedure is used to estimate the expected performance of a given design method. The unbiased performance estimates (P2) obtained for the data sets that we consider confirm that properly designed single proteochemometric models have useful predictive power, but that a standard design based on cross validation may yield models with quite limited performance. The results also show that different commercial software packages employed for the design of proteochemometric models may yield very different and therefore misleading performance estimates. In addition, the differences in the models obtained in the double CV loop indicate that detailed chemical interpretation of a single proteochemometric model is uncertain when data sets are small. Conclusion The double CV loop employed offer unbiased performance estimates about a given proteochemometric modelling procedure, making it possible to identify cases where the proteochemometric design does not result in useful predictive models. Chemical interpretations of single proteochemometric models are uncertain and should instead be based on all the models selected in the double CV loop employed here.
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| 9. |
- Fryknäs, Mårten, et al.
(författare)
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Phenotype-based screening of mechanistically annotated compounds in combination with gene expression and pathway analysis identifies candidate drug targets in a human squamous carcinoma cell model
- 2006
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Ingår i: Journal of Biomolecular Screening. - : Elsevier BV. - 1087-0571 .- 1552-454X. ; 11:5, s. 457-468
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Tidskriftsartikel (refereegranskat)abstract
- The squamous cell carcinoma HeLa cell line and an epithelial cell line hTERT-RPE with a nonmalignant phenotype were interrogated for HeLa cell selectivity in response to 1267 annotated compounds representing 56 pharmacological classes. Selective cytotoxic activity was observed for 14 of these compounds dominated by cyclic adenosine monophosphate (cAMP) selective phosphodiesterase (PDE) inhibitors, which tended to span a representation of the chemical descriptor space of the library. The PDE inhibitors induced delayed cell death with features compatible with classical apoptosis. The PDE inhibitors were largely inactive when tested against a cell line panel consisting of hematological and nonsquamous epithelial phenotypes. In a genome-wide DNA microarray analysis, PDE3A and PDE2A were found to be significantly increased in HeLa cells compared to the other cell lines. The pathway analysis software PathwayAssist was subsequently used to extract a list of proteins and small molecules retrieved from Medline abstracts associated with the hit compounds. The resulting list consisted of major parts of the cAMP-protein kinase A pathway linking to ERK, P38, and AKT. This molecular network may provide a basis for further exploitation of novel candidate targets for the treatment of squamous cell carcinoma.
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