Search results for "Pathway"
showing 10 items of 1685 documents
Show me your signaling– and I’ll tell you who you are
2009
See Article, pages 725–733Cancer research and therapy have come a long way:the field started out in search of a ‘‘magic bullet” accord-ing to Paul Ehrlich’s theory, and was hoping to identifya target which was pivotal to signaling survival in trans-formed cells. Indeed, certain diseases with monocausalmutations were identified, and targeting of the muta-tional products has helped in the design of treatmentstrategies. In chronic myeloid leukemia (CML), the con-stitutive activation of the tyrosine kinase BCR-ABL ispathognomonic [1], and multiple BCR-ABL kinaseinhibitors (e.g. imatinib mesylate, dasatinib, nilotinib)have been developed and successfully used in the treat-ment of CML offering near-…
A systems biology perspective on cholangiocellular carcinoma development: focus on MAPK-signaling and the extracellular environment.
2008
Background/Aims Multiple genes have been implicated in cholangiocellular carcinoma (CCC) development. However, the overall neoplastic risk is likely associated with a much lower number of critical physiological pathways. Methods To investigate this hypothesis, we extracted all published genetic associations for the development of CCC from PubMed (genetic association studies, but also studies associating genes and CCC in general, i.e. functional studies in cell lines, genetic studies in humans, knockout mice etc.) and integrated CCC microarray data. Results We demonstrated the MAPK pathway was consistently enriched in CCC. Comparing our data to genetic associations in HCC often successfully …
Where Does Nε-Trimethyllysine for the Carnitine Biosynthesis in Mammals Come from?
2014
N(ε)-trimethyllysine (TML) is a non-protein amino acid which takes part in the biosynthesis of carnitine. In mammals, the breakdown of endogenous proteins containing TML residues is recognized as starting point for the carnitine biosynthesis. Here, we document that one of the main sources of TML could be the vegetables which represent an important part of daily alimentation for most mammals. A HPLC-ESI-MS/MS method, which we previously developed for the analysis of N(G)-methylarginines, was utilized to quantitate TML in numerous vegetables. We report that TML, believed to be rather rare in plants as free amino acid, is, instead, ubiquitous in them and at not negligible levels. The occurrenc…
Pathway analysis of high-throughput biological data within a Bayesian network framework
2011
Abstract Motivation: Most current approaches to high-throughput biological data (HTBD) analysis either perform individual gene/protein analysis or, gene/protein set enrichment analysis for a list of biologically relevant molecules. Bayesian Networks (BNs) capture linear and non-linear interactions, handle stochastic events accounting for noise, and focus on local interactions, which can be related to causal inference. Here, we describe for the first time an algorithm that models biological pathways as BNs and identifies pathways that best explain given HTBD by scoring fitness of each network. Results: Proposed method takes into account the connectivity and relatedness between nodes of the p…
Comprehensive estimation of input signals and dynamics in biochemical reaction networks
2012
Abstract Motivation: Cellular information processing can be described mathematically using differential equations. Often, external stimulation of cells by compounds such as drugs or hormones leading to activation has to be considered. Mathematically, the stimulus is represented by a time-dependent input function. Parameters such as rate constants of the molecular interactions are often unknown and need to be estimated from experimental data, e.g. by maximum likelihood estimation. For this purpose, the input function has to be defined for all times of the integration interval. This is usually achieved by approximating the input by interpolation or smoothing of the measured data. This procedu…
Misinterpretation risks of global stochastic optimisation of kinetic models revealed by multiple optimisation runs
2016
Abstract One of use cases for metabolic network optimisation of biotechnologically applied microorganisms is the in silico design of new strains with an improved distribution of metabolic fluxes. Global stochastic optimisation methods (genetic algorithms, evolutionary programing, particle swarm and others) can optimise complicated nonlinear kinetic models and are friendly for unexperienced user: they can return optimisation results with default method settings (population size, number of generations and others) and without adaptation of the model. Drawbacks of these methods (stochastic behaviour, undefined duration of optimisation, possible stagnation and no guaranty of reaching optima) cau…
Efficient differentiation of embryonic stem cells into mesodermal precursors by BMP, retinoic acid and Notch signalling
2012
The ability to direct differentiation of mouse embryonic stem (ES) cells into specific lineages not only provides new insights into the pathways that regulate lineage selection but also has translational applications, for example in drug discovery. We set out to develop a method of differentiating ES cells into mesodermal cells at high efficiency without first having to induce embryoid body formation. ES cells were plated on a feeder layer of PA6 cells, which have membrane-associated stromal-derived inducing activity (SDIA), the molecular basis of which is currently unknown. Stimulation of ES/PA6 co-cultures with Bone Morphogenetic Protein 4 (BMP4) both favoured self-renewal of ES cells and…
Machine learning for a combined electroencephalographic anesthesia index to detect awareness under anesthesia
2020
Spontaneous electroencephalogram (EEG) and auditory evoked potentials (AEP) have been suggested to monitor the level of consciousness during anesthesia. As both signals reflect different neuronal pathways, a combination of parameters from both signals may provide broader information about the brain status during anesthesia. Appropriate parameter selection and combination to a single index is crucial to take advantage of this potential. The field of machine learning offers algorithms for both parameter selection and combination. In this study, several established machine learning approaches including a method for the selection of suitable signal parameters and classification algorithms are a…
Biologically Inspired Model for Inference of 3D Shape from Texture.
2015
A biologically inspired model architecture for inferring 3D shape from texture is proposed. The model is hierarchically organized into modules roughly corresponding to visual cortical areas in the ventral stream. Initial orientation selective filtering decomposes the input into low-level orientation and spatial frequency representations. Grouping of spatially anisotropic orientation responses builds sketch-like representations of surface shape. Gradients in orientation fields and subsequent integration infers local surface geometry and globally consistent 3D depth. From the distributions in orientation responses summed in frequency, an estimate of the tilt and slant of the local surface can…
Chronic myeloid leukemia-derived exosomes promote tumor growth through an autocrine mechanism.
2014
Background Chronic myeloid leukemia (CML) is a clonal hematopoietic stem cell disorder in which leukemic cells display a reciprocal t(9:22) chromosomal translocation that results in the formation of the chimeric BCR-ABL oncoprotein, with a constitutive tyrosine kinase activity. Consequently, BCR-ABL causes increased proliferation, inhibition of apoptosis, and altered adhesion of leukemic blasts to the bone marrow (BM) microenvironment. It has been well documented that cancer cells can generate their own signals in order to sustain their growth and survival, and recent studies have revealed the role of cancer-derived exosomes in activating signal transduction pathways involved in cancer cell…