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Sökning: LAR1:uu > (2005-2009) > Isaksson Anders

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1.
  • Andersson, Claes R., et al. (författare)
  • Bayesian detection of periodic mRNA time profiles withouth use of training examples
  • 2006
  • Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 7, s. 63-
  • 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)
  • In vitro drug sensitivity-gene expression correlations involve a tissue of origin dependency
  • 2007
  • Ingår i: Journal of chemical information and modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 47:1, s. 239-248
  • 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)
  • Revealing cell cycle control by combining model-based detection of periodic expression with novel cis-regulatory descriptors
  • 2007
  • Ingår i: BMC Systems Biology. - : Springer Science and Business Media LLC. - 1752-0509. ; 1, s. 45-
  • 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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4.
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5.
  • Fryknäs, Mårten, 1974- (författare)
  • Molecular Screening for Target Discovery in Cancer
  • 2006
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Cancer is one of the major causes of death in the western world. Resistance to anti-cancer drugs and diagnostic difficulties are major obstacles to successful treatment. This thesis describes studies based on microarray expression analysis and high-throughput compound screening for identification of resistance mechanisms, drug targets and diagnostic markers. In paper I-IV, we applied global expression analysis and measurements of drug response in a human tumor cell line panel to identify drug targets and resistance mechanisms. In paper I, we identified gene transcript levels that correlate with drug resistance and sensitivity. Both well known and new potential markers and mechanisms were identified. In paper II, we showed that STAT1 activity is associated with cross-resistance to both doxorubicin and radiation in vitro and that fludarabine can counteract STAT1 activity and reduce resistance. In Paper III-IV, cell lines were exposed to a compound library consisting of more than thousand different substances in a high-throughput screening effort. These studies revealed that cell line models of squamous cell carcinoma (Paper III) and drug resistant myeloma (Paper IV) are sensitive to phosphodiesterase inhibitors and glucocorticoids respectively. The target molecules for these drugs were over-expressed at the mRNA level and constitute likely explanations for the observed drug potency. In paper V, we identified mRNA markers for the distinction between two types of thyroid tumors, thyroid follicular adenomas and thyroid follicular carcinomas, by means of microarray expression analysis. Our results indicated that distinction between the two tumor types is possible with a small number of markers.
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6.
  • Fryknäs, Mårten, et al. (författare)
  • 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
  • Ingår i: Journal of Biomolecular Screening. - : Elsevier BV. - 1087-0571 .- 1552-454X. ; 11:5, s. 457-468
  • 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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7.
  • Fryknäs, Mårten, et al. (författare)
  • STAT1 signaling is associated with acquired crossresistance to doxorubicin and radiation in myeloma cell lines
  • 2007
  • Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 120:1, s. 189-195
  • Tidskriftsartikel (refereegranskat)abstract
    • The myeloma cell line RPMI 8226/S and its doxorubicin resistant subline 8226/Dox40 were used as models to explore the potential importance of the STAT1 signaling pathway in drug and radiation resistance. The 40-fold doxorubicin resistant subline 8226/Dox40 was found to be crossresistant to single doses of 4 and 8 Gy of radiation. A genome-wide mRNA expression study comparing the 8226/Dox40 cell line to its parental line was performed to identify the underlying molecular mechanisms. Seventeen of the top 50 overexpressed genes have previously been implicated in the STAT1 signaling pathway. STAT1 was over expressed both at the mRNA and protein level. Moreover, analyses of nuclear extracts showed higher abundance of phosphorylated STAT1 (Tyr 701) in the resistant subline. Preexposure of the crossresistant cells to the STAT1 inhibiting drug fludarabine reduced expression of overexpressed genes and enhanced the effects of both doxorubicin and radiation. These results show that resistance to doxorubicin and radiation is associated with increased STAT1 signaling and can be modulated by fludarabine. The data support further development of therapies combining fludarabine and radiation.
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8.
  • Gunnarsson, Rebeqa, et al. (författare)
  • Screening for copy-number alterations and loss of heterozygosity in chronic lymphocytic leukemia-A comparative study of four differently designed, high resolution microarray platforms
  • 2008
  • Ingår i: Genes, Chromosomes and Cancer. - : Wiley. - 1045-2257 .- 1098-2264. ; 93, s. 0536-0536
  • Tidskriftsartikel (refereegranskat)abstract
    • Screening for gene copy-number alterations (CNAs) has improved by applying genome-wide microarrays, where SNP arrays also allow analysis of loss of heterozygozity (LOH). We here analyzed 10 chronic lymphocytic leukemia (CLL) samples using four different high-resolution platforms: BAC arrays (32K), oligonucleotide arrays (185K, Agilent), and two SNP arrays (250K, Affymetrix and 317K, Illumina). Cross-platform comparison revealed 29 concordantly detected CNAs, including known recurrent alterations, which confirmed that all platforms are powerful tools when screening for large aberrations. However, detection of 32 additional regions present in 2-3 platforms illustrated a discrepancy in detection of small CNAs, which often involved reported copy-number variations. LOH analysis using dChip revealed concordance of mainly large regions, but showed numerous, small nonoverlapping regions and LOH escaping detection. Evaluation of baseline variation and copy-number ratio response showed the best performance for the Agilent platform and confirmed the robustness of BAC arrays. Accordingly, these platforms demonstrated a higher degree of platform-specific CNAs. The SNP arrays displayed higher technical variation, although this was compensated by high density of elements. Affymetrix detected a higher degree of CNAs compared to Illumina, while the latter showed a lower noise level and higher detection rate in the LOH analysis. Large-scale studies of genomic aberrations are now feasible, but new tools for LOH analysis are requested.
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9.
  • Göransson, Hanna, et al. (författare)
  • Quantification of normal cell fraction and copy number neutral LOH in clinical lung cancer samples using SNP array data
  • 2009
  • Ingår i: PloS one. - : Public Library of Science (PLoS). - 1932-6203. ; 4:6, s. e6057-
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Technologies based on DNA microarrays have the potential to provide detailed information on genomic aberrations in tumor cells. In practice a major obstacle for quantitative detection of aberrations is the heterogeneity of clinical tumor tissue. Since tumor tissue invariably contains genetically normal stromal cells, this may lead to a failure to detect aberrations in the tumor cells. PRINCIPAL FINDING: Using SNP array data from 44 non-small cell lung cancer samples we have developed a bioinformatic algorithm that accurately models the fractions of normal and tumor cells in clinical tumor samples. The proportion of normal cells in combination with SNP array data can be used to detect and quantify copy number neutral loss-of-heterozygosity (CNNLOH) in the tumor cells both in crude tumor tissue and in samples enriched for tumor cells by laser capture microdissection. CONCLUSION: Genome-wide quantitative analysis of CNNLOH using the CNNLOH Quantifier method can help to identify recurrent aberrations contributing to tumor development in clinical tumor samples. In addition, SNP-array based analysis of CNNLOH may become important for detection of aberrations that can be used for diagnostic and prognostic purposes.
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10.
  • Hagberg, Anette, et al. (författare)
  • Gene expression analysis identifies a genetic signature potentially associated with response to alpha-IFN in chronic phase CML patients
  • 2007
  • Ingår i: Leukemia research. - : Elsevier BV. - 0145-2126 .- 1873-5835. ; 31:7, s. 931-938
  • Tidskriftsartikel (refereegranskat)abstract
    • Microarray-based gene expression analysis was performed on diagnostic chronic phase CML patient samples prior to interferon treatment. Fifteen patient samples corresponding to six cytogenetic responders and nine non-responders were included. Genes differentially expressed between responder and non-responder patients were listed and a subsequent leave-one-out cross validation (LOOV) procedure showed that the top 20 genes allowed the highest prediction accuracy. The relevant genes were quantified by real-time PCR that supported the microarray results. We conclude that it might be possible to use gene expression analysis to predict future response to interferon in CML diagnostic samples.
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