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Biomedical subjects

M G Gustafsson

Publications and source records attributed to M G Gustafsson.

11 recordsLinked to original sources
PubMed2006

Computational detection of allergenic proteins attains a new level of accuracy with in silico variable-length peptide extraction and machine learning.

The placing of novel or new-in-the-context proteins on the market, appearing in genetically modified foods, certain bio-pharmaceuticals and some household products leads to human exposure to proteins that may elicit allergic responses. Accurate methods to detect allergens are therefore necessary to ensure consumer/patient safety. We demonstrate that it is possible to reach a new level of accuracy in computational detection of allergenic proteins by presenting a novel detector, Detection based on Filtered Length-adjusted Allergen Peptides (DFLAP). The DFLAP algorithm extracts variable length allergen sequence fragments and employs modern machine learning techniques in the form of a support vector machine. In particular, this new detector shows hitherto unmatched specificity when challenged to the Swiss-Prot repository without appreciable loss of sensitivity. DFLAP is also the first reported detector that successfully discriminates between allergens and non-allergens occurring in protein families known to hold both categories. Allergenicity assessment for specific protein sequences of interest using DFLAP is possible via ulfh@slv.se.

Algorithms↗
PubMed2005

Identification of molecular mechanisms for cellular drug resistance by combining drug activity and gene expression profiles.

Acquired drug resistance is a major problem in cancer treatment. To explore the genes involved in chemosensitivity and resistance, 10 human tumour cell lines, including parental cells and resistant subtypes selected for resistance against doxorubicin, melphalan, teniposide and vincristine, were profiled for mRNA expression of 7400 genes using cDNA microarray technology. The drug activity of 66 cancer agents was evaluated on the cell lines, and correlations between drug activity and gene expression were calculated and ranked. Hierarchical clustering of drugs based on their drug-gene correlations yielded clusters of drugs with similar mechanism of action. Genes correlated with drug sensitivity and resistance were imported into the PathwayAssist software to identify putative molecular pathways involved. A substantial number of both proapoptotic and antiapoptotic genes such as signal transducer and activator of transcription 1, mitogen-activated protein kinase 1 and focal adhesion kinase were found to be associated to drug resistance, whereas genes linked to cell cycle control and proliferation, such as cell division cycle 25A and signal transducer of activator of transcription 5A, were associated to general drug sensitivity. The results indicate that combined information from drug activity and gene expression in a resistance-based cell line panel may provide new knowledge of the genes involved in anticancer drug resistance and become a useful tool in drug development.

Antineoplastic Agents↗
PubMed2004

Statistical evaluation of local alignment features predicting allergenicity using supervised classification algorithms.

BACKGROUND: Recently, two promising alignment-based features predicting food allergenicity using the k nearest neighbor (kNN) classifier were reported. These features are the alignment score and alignment length of the best local alignment obtained in a database of known allergen sequences. METHODS: In the work reported here a much more comprehensive statistical evaluation of the potential of these features was performed, this time for the prediction of allergenicity in general. The evaluation consisted of the following four key components. (1) A new high quality database consisting of 318 carefully selected, non-redundant allergens and 1,007 sequences carefully selected to be non-allergens. (2) Three different supervised algorithms: the kNN classifier, the Bayesian linear Gaussian classifier, and the Bayesian quadratic Gaussian classifier. (3) A large set of local alignment procedures defined using the FASTA3 alignment program by means of a wide range of different parameter settings. (4) Novel performance curves, alternative to conventional receiver-operating characteristic curves, to display not only average behaviors but also statistical variations due to small data sets. RESULTS: The linear Gaussian classifier proved most useful among the tested supervised machine learning algorithms, closely followed by the quadratic Gaussian equivalent and kNN. The overall best classification results were obtained with a novel feature vector consisting of the combined alignment scores derived from local alignment procedures using different substitution matrices. CONCLUSIONS: The models reported here should be useful as a part of an integrated assessment scheme for potential protein allergenicity and for future comparisons with alternative bioinformatic approaches.

Algorithms↗
PubMed2001

Computational adaptive optics for live three-dimensional biological imaging.

Light microscopy of thick biological samples, such as tissues, is often limited by aberrations caused by refractive index variations within the sample itself. This problem is particularly severe for live imaging, a field of great current excitement due to the development of inherently fluorescent proteins. We describe a method of removing such aberrations computationally by mapping the refractive index of the sample using differential interference contrast microscopy, modeling the aberrations by ray tracing through this index map, and using space-variant deconvolution to remove aberrations. This approach will open possibilities to study weakly labeled molecules in difficult-to-image live specimens.

Animals↗
PubMed2000

Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy.

Lateral resolution that exceeds the classical diffraction limit by a factor of two is achieved by using spatially structured illumination in a wide-field fluorescence microscope. The sample is illuminated with a series of excitation light patterns, which cause normally inaccessible high-resolution information to be encoded into the observed image. The recorded images are linearly processed to extract the new information and produce a reconstruction with twice the normal resolution. Unlike confocal microscopy, the resolution improvement is achieved with no need to discard any of the emission light. The method produces images of strikingly increased clarity compared to both conventional and confocal microscopes.

Actins↗
PubMed1999

Extended resolution fluorescence microscopy.

Fluorescence microscopy is an essential tool of modern biology, but, like all forms of optical imaging, it is subject to physical limits on its resolving power. In recent years, several exciting techniques have been introduced to exceed these limits, including standing wave microscopy, 4Pi confocal microscopy, I5M and structured illumination microscopy. Several such techniques have been definitively demonstrated for the first time during the past year.

Animals↗
PubMed1999

I5M: 3D widefield light microscopy with better than 100 nm axial resolution.

Sevenfold improved axial resolution has been achieved in three-dimensional widefield fluorescence microscopy, using a novel interferometric technique in which the sample is observed and/or illuminated from both sides simultaneously using two opposing objective lenses. Separate interference effects in the excitation light and the emitted light give access to higher resolution axial information about the sample than can be reached by conventional widefield or confocal microscopes. Here we report the experimental verification of this resolution performance on complex biological samples.

Cytoskeleton↗
PubMed1990

Measuring changes in membrane thickness by scanning tunneling microscopy.

We investigated the feasibility of using the scanning tunneling microscope (STM) as a morphometric tool to measure the thickness of biomembranes. Planar monolayers of oriented purple membrane (PM) were prepared, nitrogen-dried or freeze-etched, and coated with metal. PM thickness was quantified by STM and transmission electron microscopy. STM calibration and the effect of contamination-mediated surface deformation on measurements of PM thickness were evaluated. The thickness of PM attached to mica and glass and the effect of papain on PM thickness were also examined. The apparent thickness of enzymatically modified PM increased after papain treatment. The mean thickness of both nitrogen-dried PM on mica and freeze-etched PM on glass was 4.6 nm. After papain treatment PM thickness on mica increased to 4.8 nm and on glass to 5.4 nm. These results demonstrate that STM analysis of metal-coated planar membrane monolayers can be used to measure changes in average membrane thickness at sub-nanometer resolution.

Amino Acids↗
PubMed1990

Scanning tunneling microscopy of planar biomembranes.

We combined planar membrane monolayer techniques with scanning tunneling microscopy (STM) to measure the thickness of metal-coated purple membrane (PM) isolated from Halobacterium halobium. Although the metal coating precluded obtaining high-resolution lateral information, it facilitated obtaining high-resolution vertical information. For example, the apparent mean thickness of planar PM and variations in thickness of enzyme-treated PM could be detected and quantified at sub-nanometer resolution.

Cell Membrane↗
PubMedDate not supplied

A probabilistic derivation of the partial least-squares algorithm.

Traditionally the partial least-squares (PLS) algorithm, commonly used in chemistry for ill-conditioned multivariate linear regression, has been derived (motivated) and presented in terms of data matrices. In this work the PLS algorithm is derived probabilistically in terms of stochastic variables where sample estimates calculated using data matrices are employed at the end. The derivation, which offers a probabilistic motivation to each step of the PLS algorithm, is performed for the general multiresponse case and without reference to any latent variable model of the response variable and also without any so-called "inner relation". On the basis of the derivation, some theoretical issues of the PLS algorithm are briefly considered: the complexity of the original motivation of PLS regression which involves an "inner relation"; the original motivation behind the prediction stage of the PLS algorithm; the relationship between uncorrelated and orthogonal latent variables; the limited possibilities to make natural interpretations of the latent variables extracted.

Journal Article↗