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See detailPrediction of genetic interactions in yeast using machine learning
Schrynemackers, Marie ULg

Conference (2009, December 14)

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See detailPrediction of genetic risk of complex diseases by supervised learning
Botta, Vincent ULg; Geurts, Pierre ULg; Hansoul, Sarah et al

Scientific conference (2008, May)

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See detailPrediction of hypertension from adolescence to adulthood : a 10 years follow-up study
Saint-Remy, Annie ULg; Rorive, Georges ULg

in CVD Epidemiology Newsletter (American Heart Association) (1992), 47

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See detailPrediction of individual methane emission by dairy cattle from mid-infrared spectra
Vanlierde, Amélie ULg; Delfosse, Camille; Dehareng, Frédéric et al

Conference (2010, July 14)

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See detailPrediction of individual methane emission by dairy cattle from mid-infrared spectra
Vanlierde, Amélie ULg; Delfosse, Camille; Dehareng, Frédéric et al

in Journal of Dairy Science, 94(E-Suppl. 1) (2011)

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See detailPrediction of knee loads using a lower extremity model based on the Klein Horsman data set
Schwartz, Cédric ULg; Lund, Morten; de Zee, Mark et al

Conference (2010, June)

In this paper, the in-vivo loads of the knee joint provided by an instrumented prosthesis (Fregly et al., 2010, Lin et al., 2010, Kim et al., 2009) are compared to the results obtained from an ... [more ▼]

In this paper, the in-vivo loads of the knee joint provided by an instrumented prosthesis (Fregly et al., 2010, Lin et al., 2010, Kim et al., 2009) are compared to the results obtained from an implementation of the Klein Horsman data set (2007) in the AnyBody Modeling System. The lateral and medial knee contact forces are estimated directly from the knee modeled as a modified revolute joint. As such, this study presents what can be achieved by estimating the knee contact forces from a simplified knee model. [less ▲]

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See detailPrediction of landslide susceptibility in a seismically active high mountain region using data mining methods - a study from Maily-Say, Kyrgyzstan
Braun, Anika; Fernandez-Steeger, Tomas; Havenith, Hans-Balder ULg et al

in Reicherter, Klaus; Rudersdorf, Andreas; Grützner, Christoph (Eds.) Seismic Hazard, Critical Facilities and Slow Active Faults, Proceedings (2013, October)

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See detailPrediction of macroscopic mechanical properties of a polycrystalline microbeam subjected to material uncertainties
Lucas, Vincent ULg; Wu, Ling ULg; Arnst, Maarten ULg et al

in Cunha, Álvaro; Caetano, Elsa; Ribeiro, Pedro (Eds.) et al Proceedings of the 9th International Conference on Structural Dynamics, EURODYN 2014 (2014, June)

The first resonance frequency is a key performance characteristic of MEMS vibrometers. In batch fabrication, this first resonance frequency can exhibit scatter owing to various sources of manufacturing ... [more ▼]

The first resonance frequency is a key performance characteristic of MEMS vibrometers. In batch fabrication, this first resonance frequency can exhibit scatter owing to various sources of manufacturing variability involved in the fabrication process. The aim of this work is to develop a stochastic multiscale model for predicting the first resonance frequency of MEMS microbeams constituted of polycrystals while accounting for the uncertainties in the microstructure due to the grain orientations. At the finest scale, we model the microstructure of polycrystaline materials using a random Voronoï tessellation, each grain being assigned a random orientation. Then, we apply a computational homogenization procedure on statistical volume elements to obtain a stochastic characterization of the elasticity tensor at the second scale of interest, the meso-scale. In the future, using a stochastic finite element method, we will propagate these meso-scale uncertainties to the first resonance frequency at the coarser scale. [less ▲]

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See detailPrediction of maternal predisposition to preeclampsia
Emonts, Patrick ULg; Seaksan, S.; Seidel, Laurence ULg et al

in Hypertension in Pregnancy : Official Journal of the International Society for the Study of Hypertension in Pregnancy (2008), 27(3), 237-45

Objective: To derive a prediction index based on the most salient patient history, laboratory, and clinical parameters for identifying women at high risk for developing preeclampsia (PE). Methods ... [more ▼]

Objective: To derive a prediction index based on the most salient patient history, laboratory, and clinical parameters for identifying women at high risk for developing preeclampsia (PE). Methods: Nonpregnant women with a history of PE (n = 101) were compared with nonpregnant parous women with a history of one or more successful normotensive pregnancies (n = 50) but with comparable age, gestation, and parity profiles. The parameters included a medical examination (demographics, patient history, family history, and clinical and obstetrical findings), laboratory investigations (hemostasis, coagulation, and vitamins), and morphological and functional tests (cardiovascular and renal functions). Stepwise logistic regression analysis was applied to develop a three-step PE prediction index based on the most discriminant parameters. Results: Patients with and without PE differed significantly (p < 0.05) with respect to 1) maternal history of chronic hypertension, body mass index, and blood pressure; 2) APTT, PT, activated factor VIII, homocystein, free protein S and vitamin B1; and 3) relative plasma volume. Based on these three sets of parameters, a three-step PE prediction index was developed. The likelihood ratio of a positive index score was equal to 3.4, 7.3, and 8.8, respectively. Thus, assuming a PE prevalence (or prior probability) of 5%, a patient's chances of developing PE when presenting with a positive score on the three-step prediction index were 15%, 28%, and 32%, respectively. Discussion: In the absence of welldefined pre-pregnancy screening guidelines for PE, the present study attempts to proceed in a stepwise fashion by looking at medical examination data first, requesting, if necessary, specific hemostasis and coagulation tests next, and finally measuring the relative plasma volume for confirmatory purposes. This approach offers a satisfactory positive predictive value and cost efficiency ratio. [less ▲]

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See detailPrediction of maximum loads due to turbulent gusts using nonlinear system identification
Dimitriadis, Grigorios ULg; Cooper, J. E.

in Proceedings of the 1997 International Forum on Aeroelasticity and Structural Dynamics (1997, June)

Two nonlinear system identification methods, the NARMAX method and a proposed method based on the Restoring Force Surface method, were used in conjunction with two gust load prediction methods, the ... [more ▼]

Two nonlinear system identification methods, the NARMAX method and a proposed method based on the Restoring Force Surface method, were used in conjunction with two gust load prediction methods, the Matched Filter Based 1-dimensional search and the Deterministic Spectral procedure - or Matched Filter Based multi-dimensional search - in order to demonstrate the feasibility of obtaining maximised gust loads using identified models of nonlinear aeroelastic systems. The procedure was tried on two different mathematical systems, a simple, one-degree-of-freedom system with cubic nonlinearity and a model of a wing with control surface and discontinuous nonlinearities. The maximised gust loads predicted from the identified systems were very close to the ones obtained for the actual systems. Furthermore, it was demonstrated that performing the identification procedure at low excitation levels does not adversely affect the prediction of the maximised loads and critical gust profiles. [less ▲]

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See detailPrediction of mean and turbulent kinetic energy in rectangular shallow reservoirs
Camnasio, Erica; Erpicum, Sébastien ULg; Archambeau, Pierre ULg et al

in Engineering Applications of Computational Fluid Mechanics (2014), 8(4),

Shallow rectangular reservoirs are common structures in urban hydraulics and river engineering. Despite their simple geometry, complex symmetric and asymmetric flow fields develop in such reservoirs ... [more ▼]

Shallow rectangular reservoirs are common structures in urban hydraulics and river engineering. Despite their simple geometry, complex symmetric and asymmetric flow fields develop in such reservoirs, depending on their expansion ratio and length-to-width ratio. The original contribution of this study is the analysis of the kinetic energy content of the mean flow, based on UVP velocity measurements carried throughout the reservoir in eleven different geometric configurations. A new relationship is derived between the specific mean kinetic energy and the reservoir shape factor. For most considered geometric configurations, leading to four different flow patterns, the experimentally observed flow fields and mean kinetic energy contents are successfully reproduced by an operational numerical model based on the depth-averaged flow equations and a two-length-scale k-e turbulence closure. The analysis also highlights the better performance of this depth-averaged k-e model compared to an algebraic turbulence model. Finally, the turbulent kinetic energy in the reservoir is derived from the experimental measurements and the corresponding numerical predictions based on the k-e model agree satisfactorily in the main jet but not in the recirculation zones. [less ▲]

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See detailPrediction of mean skin temperature in warm environments
Mairiaux, Philippe ULg; Malchaire, J.; Candas, V.

in European Journal of Applied Physiology and Occupational Physiology (1987), 56(6), 686-92

The data collected by the authors in four experimental series have been analysed together with data from the literature, to study the relationship between mean skin temperature and climatic parameters ... [more ▼]

The data collected by the authors in four experimental series have been analysed together with data from the literature, to study the relationship between mean skin temperature and climatic parameters, subject metabolic rate and clothing insulation. The subjects involved in the various studies were young male subjects, unacclimatized to heat. The range of conditions examined involved mean skin temperatures between 33 degrees C and 38 degrees C, air temperatures (Ta) between 23 degrees C and 50 degrees C, ambient water vapour pressures (Pa) between 1 and 4.8 kPa, air velocities (Va) between 0.2 and 0.9 m.s-1, metabolic rates (M) between 50 and 270 W.m-2, and Clo values between 0.1 and 0.6. In 95% of the data, mean radiant temperature was within +/- 3 degrees C of air temperature. Based on 190 data averaged over individual values, the following equation was derived by a multiple linear regression technique: Tsk = 30.0 + 0.138 Ta + 0.254 Pa-0.57 Va + 1.28.10(-3) M-0.553 Clo. This equation was used to predict mean skin temperature from 629 individual data. The difference between observed and predicted values was within +/- 0.6 degrees C in 70% of the cases and within +/- 1 degrees C in 90% of the cases. It is concluded that the proposed formula may be used to predict mean skin temperature with satisfactory accuracy in nude to lightly clad subjects exposed to warm ambient conditions with no significant radiant heat load. [less ▲]

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See detailPrediction Of Membrane Protein Orientation In Lipid Bilayers: A Theoretical Approach
Basyn, F.; Charloteaux, Benoît ULg; Thomas, Annick ULg et al

in Journal of Molecular Graphics & Modelling (2001), 20(3), 235-44

Over the past few years, several three-dimensional (3-D) structures of membrane proteins have been described with increasing accuracy, but their relationship with membranes are still not well understood ... [more ▼]

Over the past few years, several three-dimensional (3-D) structures of membrane proteins have been described with increasing accuracy, but their relationship with membranes are still not well understood. Recently, we have developed an empirical method, Integral Membrane Protein and Lipid Association (IMPALA), to predict the insertion of molecules (lipids, drugs) into lipid bilayers (Proteins 30 (1998) 357). The IMPALA uses a Monte Carlo minimisation procedure to calculate the depth and the angle of insertion of membrane-interacting molecules taking into account the restraints dictated by a lipid bilayer. In this paper, we use IMPALA to test the insertion of 23 integral membranous proteins (IMPs) and 2 soluble proteins into membranes. Four IMP are studied in detail: OmpA, maltoporin, MsCl channel and bacteriorhodopsin. The 3-D structures of the proteins are kept constant and the insertion into membrane is monitored by minimising the value of the restraint representing the sum of two terms, one for lipid perturbation and the other for hydrophobicity. The two soluble proteins are rejected from the membrane whereas, under the same conditions, all the membrane proteins remain inside, if the solvent accessible surface of the amino acids located inside the pore of porins is ignored. The results give the tilt angle of the IMP helices or strands with respect to the membrane surface and the depth of the protein mass centre insertion. We conclude that the restraint terms of IMPALA could be used to study the insertion of model structures or complexes of proteins within membranes. [less ▲]

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See detailPrediction of membrane protein structures and TM interactions Rosetta and molecular dynamic studies
Crowet, Jean-Marc ULg; Dony, Nicolas ULg; Joris, Bernard ULg et al

Poster (2013, February 26)

The structures of membrane domains of the Divisome proteins and BlaR are not known and there is no homolog proteins of known structure to build homolgy models. Although the structure prediction of ... [more ▼]

The structures of membrane domains of the Divisome proteins and BlaR are not known and there is no homolog proteins of known structure to build homolgy models. Although the structure prediction of membrane proteins seems easier than for globular proteins, their ab initio prediction remains a difficult task. Only few methods have been used and validated on experimental pdb structures. By using the MARTINI or Bond coarse grain representation, the multimerization of transmembrane helices has been carried out by molecular dynamics, and the structure of several membrane proteins has been predicted by a tool of the Rosetta package. These methods are used here to predict the structure of the membrane embedded part of the politopic proteins from the divisome (FtsW, FtsK, FtsX and MraY) and BlaR. In a following part the MARTINI force field can be used to predict the TM helices interactions between the Divisome protein members. [less ▲]

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See detailPrediction of meso-scale mechanical properties of poly-silicon materials
Lucas, Vincent ULg; Wu, Ling ULg; Arnst, Maarten ULg et al

Conference (2014, August 27)

The miniature sizes of micro–electro–mechanical systems (MEMS) as well as the nature of their manufacturing processes, such as etching, material layer deposition, or embossing, are responsible for the ... [more ▼]

The miniature sizes of micro–electro–mechanical systems (MEMS) as well as the nature of their manufacturing processes, such as etching, material layer deposition, or embossing, are responsible for the existence of a scatter in the final dimensions, material properties ... of manufactured micro–sensors. This scatter is potentially threatening the behavior and reliability of samples from a batch fabrication process, motivating the development of non-deterministic computational approaches to predict the MEMS properties. In this work we extract the meso-scale properties of the poly-silicon material under the form of a probabilistic distribution. To this end, Statistical Volume Elements (SVE) of the micro-structure are generated under the form of a Voronoï tessellation with a random orientation for each silicon grain. Hence, a Monte-Carlo procedure combined with a homogenization technique allows a distribution of the material tensor at the meso-scale to be estimated. As the finite element method is used to discretize the SVE and to solve the micro-scale boundary value problem, the homogenization technique used to extract the material tensor relies on the computational homogenization theory. In a future work, we will investigate, in the context of MEMS vibrometers, the propagation to the macro–scale of the meso-scale distribution of the homogenized elasticity tensor, with the final aim of predicting the uncertainty on their resonance frequencies. [less ▲]

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See detailPREDICTION OF MISSING MARKERS WITH LOW DENSITY MARKER PANELS IN DAIRY CATTLE
Zhang, Zhiyan; Georges, Michel ULg; Druet, Tom ULg

in Proceedings of the 9th World Congress oN Genetics Applied to Livestock Production (2010)

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See detailPrediction of monomer isomery in Florine: a workflow dedicated to nonribosomal peptide discovery.
Caradec, Thibault; Pupin, Maude; Vanvlassenbroeck, Aurelien et al

in PloS one (2014), 9(1), 85667

Nonribosomal peptides represent a large variety of natural active compounds produced by microorganisms. Due to their specific biosynthesis pathway through large assembly lines called NonRibosomal Peptide ... [more ▼]

Nonribosomal peptides represent a large variety of natural active compounds produced by microorganisms. Due to their specific biosynthesis pathway through large assembly lines called NonRibosomal Peptide Synthetases (NRPSs), they often display complex structures with cycles and branches. Moreover they often contain non proteogenic or modified monomers, such as the D-monomers produced by epimerization. We investigate here some sequence specificities of the condensation (C) and epimerization (E) domains of NRPS that can be used to predict the possible isomeric state (D or L) of each monomer in a putative peptide. We show that C- and E- domains can be divided into 2 sub-regions called Up-Seq and Down-Seq. The Up-Seq region corresponds to an InterPro domain (IPR001242) and is shared by C- and E-domains. The Down-Seq region is specific to the enzymatic activity of the domain. Amino-acid signatures (represented as sequence logos) previously described for complete C-and E-domains have been restricted to the Down-Seq region and amplified thanks to additional sequences. Moreover a new Down-Seq signature has been found for Ct-domains found in fungi and responsible for terminal cyclization of the peptides. The identification of these signatures has been included in a workflow named Florine, aimed to predict nonribosomal peptides from NRPS sequence analyses. In some cases, the prediction of isomery is guided by genus-specific rules. Florine was used on a Pseudomonas genome to allow the determination of the type of pyoverdin produced, the update of syringafactin structure and the identification of novel putative products. [less ▲]

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See detailPrediction of mortality after myocardial infarction by simple clinical variables recorded during hospitalization.
PIERARD, Luc ULg; DUBOIS, Christophe ULg; Albert, Adelin ULg et al

in Clinical Cardiology : International Journal for Cardiovascular Diseases (1989), 12(9), 500-4

Simple clinical variables obtainable in any coronary care unit and in any patient were recorded in 769 consecutive patients who were admitted with acute myocardial infarction (AMI) and who were discharged ... [more ▼]

Simple clinical variables obtainable in any coronary care unit and in any patient were recorded in 769 consecutive patients who were admitted with acute myocardial infarction (AMI) and who were discharged from the hospital and followed for up to 3 years. To identify the patients at highest and lowest risk of posthospital mortality, a prognostic index was established from a stepwise logistic discriminant analysis of variables obtained in a consecutive series of 418 patients discharged alive from one of two coronary care units admitting new patients on alternate days. This prognostic index was validated by applying it to a comparison group of 351 consecutive control patients discharged from the other coronary care unit. In the training group, 59 of the 418 patients (14%) died during the first year after hospital discharge and 34 (8%) died during the second or third year. The stepwise logistic discriminant analysis made it possible to distinguish between 1-year survivors and nonsurvivors, but not between the patients who died during the second and third years and the 3-year survivors. Four variables were selected for obtaining a 1-year prognostic index: the maximum grade of left ventricular function during hospitalization (0 to 4), history of previous AMI (1 or 0), predischarge cardiothoracic ratio (0 to 0.99), and complete bundle branch block (1 or 0). Prognostic index = 7.0196-0.6515 function - 1.6623 previous AMI - 0.0729 cardiothoracic ratio - 1.0813 bundle branch block. This index was validated in the comparison group.(ABSTRACT TRUNCATED AT 250 WORDS) [less ▲]

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See detailPrediction of new bioactive molecules using a Bayesian belief network.
Abdo, Ammar; Leclere, Valerie; Jacques, Philippe ULg et al

in Journal of chemical information and modeling (2014), 54(1), 30-6

Natural products and synthetic compounds are a valuable source of new small molecules leading to novel drugs to cure diseases. However identifying new biologically active small molecules is still a ... [more ▼]

Natural products and synthetic compounds are a valuable source of new small molecules leading to novel drugs to cure diseases. However identifying new biologically active small molecules is still a challenge. In this paper, we introduce a new activity prediction approach using Bayesian belief network for classification (BBNC). The roots of the network are the fragments composing a compound. The leaves are, on one side, the activities to predict and, on another side, the unknown compound. The activities are represented by sets of known compounds, and sets of inactive compounds are also used. We calculated a similarity between an unknown compound and each activity class. The more similar activity is assigned to the unknown compound. We applied this new approach on eight well-known data sets extracted from the literature and compared its performance to three classical machine learning algorithms. Experiments showed that BBNC provides interesting prediction rates (from 79% accuracy for high diverse data sets to 99% for low diverse ones) with a short time calculation. Experiments also showed that BBNC is particularly effective for homogeneous data sets but has been found to perform less well with structurally heterogeneous sets. However, it is important to stress that we believe that using several approaches whenever possible for activity prediction can often give a broader understanding of the data than using only one approach alone. Thus, BBNC is a useful addition to the computational chemist's toolbox. [less ▲]

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See detailPrediction of non-linear time-variant dynamic crop model using bayesian methods
Mansouri, Majdi ULg; Dumont, Benjamin ULg; Destain, Marie-France ULg

in John Stafford (Ed.) Precision agriculture '13 (2013, July)

This work addresses the problem of predicting a non-linear time-variant leaf area index and soil moisture model (LSM) using state estimation. These techniques include the extended Kalman filter (EKF ... [more ▼]

This work addresses the problem of predicting a non-linear time-variant leaf area index and soil moisture model (LSM) using state estimation. These techniques include the extended Kalman filter (EKF), particle filter (PF) and the more recently developed technique, variational filter (VF). In the comparative study, the state variables (the leaf-area index LAI, the volumetric water content of the layer 1, HUR1 and the volumetric water content of the layer 2, HUR2) are estimated from noisy measurements of these variables, and the various estimation techniques are compared by computing the estimation root mean square error with respect to the noise-free data. The results show that VF provides a significant improvement over EKF and PF. [less ▲]

Detailed reference viewed: 38 (7 ULg)