Resampling methods for parameter-free and robust feature selection with mutual information

Combining the mutual information criterion with a forward feature selection strategy offers a good trade-off between optimality of the selected feature subset and computation time. However, it requires to set the parameter(s) of the mutual information estimator and to determine when to halt the forward procedure. These two choices are difficult to make because, as the dimensionality of the subset increases, the estimation of the mutual information becomes less and less reliable. This paper proposes to use resampling methods, a K-fold cross-validation and the permutation test, to address both issues. The resampling methods bring information about the variance of the estimator, information which can then be used to automatically set the parameter and to calculate a threshold to stop the forward procedure. The procedure is illustrated on a synthetic dataset as well as on real-world examples

Violacein Induces Death of Resistant Leukaemia Cells via Kinome Reprogramming, Endoplasmic Reticulum Stress and Golgi Apparatus Collapse

It is now generally recognised that different modes of programmed cell death (PCD) are intimately linked to the cancerous process. However, the mechanism of PCD involved in cancer chemoprevention is much less clear and may be different between types of chemopreventive agents and tumour cell types involved. Therefore, from a pharmacological view, it is crucial during the earlier steps of drug development to define the cellular specificity of the candidate as well as its capacity to bypass dysfunctional tumoral signalling pathways providing insensitivity to death stimuli. Studying the cytotoxic effects of violacein, an antibiotic dihydro-indolone synthesised by an Amazon river Chromobacterium, we observed that death induced in CD34(+)/c-Kit(+)/P-glycoprotein(+)/MRP1(+) TF1 leukaemia progenitor cells is not mediated by apoptosis and/or autophagy, since biomarkers of both types of cell death were not significantly affected by this compound. To clarify the working mechanism of violacein, we performed kinome profiling using peptide arrays to yield comprehensive descriptions of cellular kinase activities. Pro-death activity of violacein is actually carried out by inhibition of calpain and DAPK1 and activation of PKA, AKT and PDK, followed by structural changes caused by endoplasmic reticulum stress and Golgi apparatus collapse, leading to cellular demise. Our results demonstrate that violacein induces kinome reprogramming, overcoming death signaling dysfunctions of intrinsically resistant human leukaemia cells.TopInstitute pharma (The Netherlands)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Dutch Cancer SocietyErasmus MC Univ Med Ctr, Dept Gastroenterol & Hepatol, Rotterdam, NetherlandsUniv Amsterdam, Acad Med Ctr, Ctr Expt & Mol Med, NL-1105 AZ Amsterdam, NetherlandsUniv Estadual Campinas, Brazil UNICAMP, Dept Biochem, Inst Biol, São Paulo, BrazilFed Univ São Paulo UNIFESP, Dept Biochem, São Paulo, BrazilFed Univ São Paulo UNIFESP, Dept Cell Biol, São Paulo, BrazilUniv Grande Rio UNIGRANRIO, Heath Sci Sch, Multidisciplinary Lab Dent Res, Rio de Janeiro, BrazilNatl Inst Metrol Qual & Technol Inmetro, Biotechnol Lab, Bioengn Sect, Rio de Janeiro, BrazilUniv Campinas UNICAMP, Inst Chem, Biol Chem Lab, Rio de Janeiro, BrazilUniv Groningen, Univ Med Ctr Groningen, Dept Pediat Oncol, Beatrix Childrens Hosp, Groningen, NetherlandsFed Univ São Paulo UNIFESP, Dept Biochem, São Paulo, BrazilFed Univ São Paulo UNIFESP, Dept Cell Biol, São Paulo, BrazilDutch Cancer Society: EMCR 2010-4737Web of Scienc

Comparison of Peptide Array Substrate Phosphorylation of c-Raf and Mitogen Activated Protein Kinase Kinase Kinase 8

Kinases are pivotal regulators of cellular physiology. The human genome contains more than 500 putative kinases, which exert their action via the phosphorylation of specific substrates. The determinants of this specificity are still only partly understood and as a consequence it is difficult to predict kinase substrate preferences from the primary structure, hampering the understanding of kinase function in physiology and prompting the development of technologies that allow easy assessment of kinase substrate consensus sequences. Hence, we decided to explore the usefulness of phosphorylation of peptide arrays comprising of 1176 different peptide substrates with recombinant kinases for determining kinase substrate preferences, based on the contribution of individual amino acids to total array phosphorylation. Employing this technology, we were able to determine the consensus peptide sequences for substrates of both c-Raf and Mitogen Activated Protein Kinase Kinase Kinase 8, two highly homologous kinases with distinct signalling roles in cellular physiology. The results show that although consensus sequences for these two kinases identified through our analysis share important chemical similarities, there is still some sequence specificity that could explain the different biological action of the two enzymes. Thus peptide arrays are a useful instrument for deducing substrate consensus sequences and highly homologous kinases can differ in their requirement for phosphorylation events

Predicting S&P 500 based on its constituents and their social media derived sentiment

Collective intelligence, represented as sentiment extracted from social media mining, is encountered in various applications. Numerous studies involving machine learning modelling have demonstrated that such sentiment information may or may not have predictive power on the stock market trend, depending on the application and the data used. This work proposes, for the first time, an approach to predicting S&P 500 based on the closing stock prices and sentiment data of the S&P 500 constituents. One of the significant complexities of our framework is due to the high dimensionality of the dataset to analyse, which is based on a large number of constituents and their sentiments, and their lagging. Another significant complexity is due to the fact that the relationship between the response and the explanatory variables is time-varying in the highly volatile stock market data, and it is difficult to capture. We propose a predictive modelling approach based on a methodology specifically designed to effectively address the above challenges and to devise efficient predictive models based on Jordan and Elman recurrent neural networks. We further propose a hybrid trading model that incorporates a technical analysis, and the application of machine learning and evolutionary optimisation techniques. We prove that our unprecedented and innovative constituent and sentiment based approach is efficient in predicting S&P 500, and thus may be used to maximise investment portfolios regardless of whether the market is bullish or bearish

Improved standardization of flow cytometry diagnostic screening of primary immunodeficiency by software-based automated gating

BackgroundMultiparameter flow cytometry (FC) is essential in the diagnostic work-up and classification of primary immunodeficiency (PIDs). The EuroFlow PID Orientation tube (PIDOT) allows identification of all main lymphocyte subpopulations in blood. To standardize data analysis, tools for Automated Gating and Identification (AG&I) of the informative cell populations, were developed by EuroFlow. Here, we evaluated the contribution of these innovative AG&I tools to the standardization of FC in the diagnostic work-up of PID, by comparing AG&I against expert-based (EuroFlow-standardized) Manual Gating (MG) strategy, and its impact on the reproducibility and clinical interpretation of results.MethodsFC data files from 44 patients (13 CVID, 12 PID, 19 non-PID) and 26 healthy donor (HD) blood samples stained with PIDOT were analyzed in parallel by MG and AG&I, using Infinicyt (TM) software (Cytognos). For comparison, percentage differences in absolute cell counts/mu L were calculated for each lymphocyte subpopulation. Data files showing differences >20% were checked for their potential clinical relevance, based on age-matched percentile (p5-p95) reference ranges. In parallel, intra- and inter-observer reproducibility of MG vs AG&I were evaluated in a subset of 12 samples.ResultsThe AG&I approach was able to identify the vast majority of lymphoid events (>99%), associated with a significantly higher intra- and inter-observer reproducibility compared to MG. For most HD (83%) and patient (68%) samples, a high degree of agreement (<20% numerical differences in absolute cell counts/mu L) was obtained between MG and the AG&I module. This translated into a minimal impact (<5% of observations) on the final clinical interpretation. In all except three samples, extended expert revision of the AG&I approach revealed no error. In the three remaining samples aberrant maturation and/or abnormal marker expression profiles were seen leading in all three cases to numerical alarms by AG&I.ConclusionAltogether, our results indicate that replacement of MG by the AG&I module would be associated with a greater reproducibility and robustness of results in the diagnostic work-up of patients suspected of PID. However, expert revision of the results of AG&I of PIDOT data still remains necessary in samples with numerical alterations and aberrant B- and T-cell maturation and/or marker expression profiles.Stemcel biology/Regenerative medicine (incl. bloodtransfusion

Are Small GTPases Signal Hubs in Sugar-Mediated Induction of Fructan Biosynthesis?

External sugar initiates biosynthesis of the reserve carbohydrate fructan, but the molecular processes mediating this response remain obscure. Previously it was shown that a phosphatase and a general kinase inhibitor hamper fructan accumulation. We use various phosphorylation inhibitors both in barley and in Arabidopsis and show that the expression of fructan biosynthetic genes is dependent on PP2A and different kinases such as Tyr-kinases and PI3-kinases. To further characterize the phosphorylation events involved, comprehensive analysis of kinase activities in the cell was performed using a PepChip, an array of >1000 kinase consensus substrate peptide substrates spotted on a chip. Comparison of kinase activities in sugar-stimulated and mock(sorbitol)-treated Arabidopsis demonstrates the altered phosphorylation of many consensus substrates and documents the differences in plant kinase activity upon sucrose feeding. The different phosphorylation profiles obtained are consistent with sugar-mediated alterations in Tyr phosphorylation, cell cycling, and phosphoinositide signaling, and indicate cytoskeletal rearrangements. The results lead us to infer a central role for small GTPases in sugar signaling

Kinome Profiling Reveals an Interaction Between Jasmonate, Salicylate and Light Control of Hyponastic Petiole Growth in Arabidopsis thaliana

Plants defend themselves against infection by biotic attackers by producing distinct phytohormones. Especially jasmonic acid (JA) and salicylic acid (SA) are well known defense-inducing hormones. Here, the effects of MeJA and SA on the Arabidopsis thaliana kinome were monitored using PepChip arrays containing kinase substrate peptides to analyze posttranslational interactions in MeJA and SA signaling pathways and to test if kinome profiling can provide leads to predict posttranslational events in plant signaling. MeJA and SA mediate differential phosphorylation of substrates for many kinase families. Also some plant specific substrates were differentially phosphorylated, including peptides derived from Phytochrome A, and Photosystem II D protein. This indicates that MeJA and SA mediate cross-talk between defense signaling and light responses. We tested the predicted effects of MeJA and SA using light-mediated upward leaf movement (differential petiole growth also called hyponastic growth). We found that MeJA, infestation by the JA-inducing insect herbivore Pieris rapae, and SA suppressed low light-induced hyponastic growth. MeJA and SA acted in a synergistic fashion via two (partially) divergent signaling routes. This work demonstrates that kinome profiling using PepChip arrays can be a valuable complementary ∼omics tool to give directions towards predicting behavior of organisms after a given stimulus and can be used to obtain leads for physiological relevant phenomena in planta