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See detailComputational modeling in tissue engineering
Geris, Liesbet ULg

Book published by Springer - 1 (2013)

One of the major challenges in tissue engineering is the translation of biological knowledge on complex cell and tissue behavior into a predictive and robust engineering process. Mastering this complexity ... [more ▼]

One of the major challenges in tissue engineering is the translation of biological knowledge on complex cell and tissue behavior into a predictive and robust engineering process. Mastering this complexity is an essential step towards clinical applications of tissue engineering. This volume discusses computational modeling tools that allow studying the biological complexity in a more quantitative way. More specifically, computational tools can help in: (i) quantifying and optimizing the tissue engineering product, e.g. by adapting scaffold design to optimize micro-environmental signals or by adapting selection criteria to improve homogeneity of the selected cell population; (ii) quantifying and optimizing the tissue engineering process, e.g. by adapting bioreactor design to improve quality and quantity of the final product; and (iii) assessing the influence of the in vivo environment on the behavior of the tissue engineering product, e.g. by investigating vascular ingrowth. The book presents examples of each of the above mentioned areas of computational modeling. The underlying tissue engineering applications will vary from blood vessels over trachea to cartilage and bone. For the chapters describing examples of the first two areas, the main focus is on (the optimization of) mechanical signals, mass transport and fluid flow encountered by the cells in scaffolds and bioreactors as well as on the optimization of the cell population itself. In the chapters describing modeling contributions in the third area, the focus will shift towards the biology, the complex interactions between biology and the micro-environmental signals and the ways in which modeling might be able to assist in investigating and mastering this complexity. The chapters cover issues related to (multiscale/multiphysics) model building, training and validation, but also discuss recent advances in scientific computing techniques that are needed to implement these models as well as new tools that can be used to experimentally validate the computational results. [less ▲]

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See detailComputational modeling under uncertainty: challenges and opportunities
Gomez-Cabrero, David; Geris, Liesbet ULg

in Modeling under uncertainty: a computational modeling approach (2015)

Computational Biology has increasingly become an important tool for biomedical and translational research. In particular, when generating novel hypothesis despite fundamental uncertainties in data and ... [more ▼]

Computational Biology has increasingly become an important tool for biomedical and translational research. In particular, when generating novel hypothesis despite fundamental uncertainties in data and mechanistic understanding of biological processes underpinning diseases. While in the present book, we have reviewed the necessary background and existing novel methodologies that set the basis for dealing with uncertainty, there are still many “grey”, or less well-defined, areas of investigations offering both challenges and opportunities. This final chapter in the book provides some reflections on those areas, namely: (1) the need for novel robust mathematical and statistical methodologies to generate hypothesis under uncertainty; (2) the challenge of aligning those methodologies in a context that requires larger computational resources; (3) the accessibility of modeling tools for less mathematical literate researchers; and (4) the integration of models with –omics data and its application in clinical environments. [less ▲]

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See detailComputational modelling of aneurysm risk in giant cell arteritis (GCA)
Manhas, Varun ULg; Piper, Jennifer; Singh, Surjeet et al

Scientific conference (2013, September)

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See detailComputational modelling of biomaterial surface interactions with blood platelets and osteoblastic cells for the prediction of contact osteogenesis.
Amor, N.; Geris, Liesbet ULg; Vander Sloten, J. et al

in Acta Biomaterialia (2011), 7(2), 779-90

Surface microroughness can induce contact osteogenesis (bone formation initiated at the implant surface) around oral implants, which may result from different mechanisms, such as blood platelet ... [more ▼]

Surface microroughness can induce contact osteogenesis (bone formation initiated at the implant surface) around oral implants, which may result from different mechanisms, such as blood platelet-biomaterial interactions and/or interaction with (pre-)osteoblast cells. We have developed a computational model of implant endosseous healing that takes into account these interactions. We hypothesized that the initial attachment and growth factor release from activated platelets is crucial in achieving contact osteogenesis. In order to investigate this, a computational model was applied to an animal experiment [7] that looked at the effect of surface microroughness on endosseous healing. Surface-specific model parameters were implemented based on in vitro data (Lincks et al. Biomaterials 1998;19:2219-32). The predicted spatio-temporal patterns of bone formation correlated with the histological data. It was found that contact osteogenesis could not be predicted if only the osteogenic response of cells was up-regulated by surface microroughness. This could only be achieved if platelet-biomaterial interactions were sufficiently up-regulated as well. These results confirmed our hypothesis and demonstrate the added value of the computational model to study the importance of surface-mediated events for peri-implant endosseous healing. [less ▲]

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See detailComputational modelling of calcium mediated bone regeneration
Carlier, Aurélie ULg; Chai, Yoke Chin; Theys, Tina et al

Poster (2010, November 26)

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See detailComputational modelling of peri-implant bone healing considering cell-biomaterial interactions
Amor, Nadya; Geris, Liesbet ULg; Vander Sloten, Jos et al

in Arbor, Ann (Ed.) Proceedings of the North American Congress on Biomechanics (2008)

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See detailComputational modelling of peri-implant healing
Amor, Nadia; Geris, Liesbet ULg; Vander Sloten, Jos et al

in Middleton, J.; Jones, M. L.; Shrive, N. (Eds.) Proceedings of the 8th interantional symposium on Computer Methods in Biomechanics and Biomedical Engineering (2008)

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See detailComputational Optimisation for Zero Energy Building Design, Interviews with Twenty Eight International Experts
Attia, Shady ULg

Report (2012)

Given the implication of designing Net Zero Energy Buildings (NZEBs), which involves complex passive and active design strategies, the use of computational automated optimization techniques is becoming ... [more ▼]

Given the implication of designing Net Zero Energy Buildings (NZEBs), which involves complex passive and active design strategies, the use of computational automated optimization techniques is becoming more essential. Therefore, this structured interviews aims to assess gaps, needs and problems considering the integration of optimization techniques to support the design of NZEBs. This work is part of the International Energy Agency (IEA) Task 40: Towards Net Zero Energy Buildings Subtask B. The objective of this report is to gain an understanding of how experts currently use optimization tools, which tools they use, the major limitations they have encountered, and their vision for the future of optimization of Net Zero Energy Buildings. With this information disseminated, it is anticipated that soft ware developers will be better informed of the needs of building design processionals. A qualitative study design was employed, using semi structured interviews. Optimization experts working in academia and practice were recruited. The participants were identified from the IBPSA Conference Proceedings between 1995 and 2010. A sampling framework was developed to include experts in the study from Europe and North America. These groups represented the range of possible optimization users, from researchers and designers considered optimization in the design of net zero or high performance buildings. A list of potential optimization experts was created and circulated between the IEA Task 40 Subtask members. Also every interviewed expert was asked to revise the list and add any potential candidate to be interviewed. [less ▲]

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See detailComputational Optimisation for Zero Energy Buildings Design Interviews results with twenty eight International expert
Attia, Shady ULg; Hamdy, Mohamed; O’Brien, William et al

in Proceedings of the 13th Conference of International Building Performance Simulation Association (2013, August)

This paper summarizes a study that was undertaken to reveal potential challenges and opportunities for integrating optimisation tools in Net/Nearly Zero Energy Buildings (NZEB) Design. The paper reviews ... [more ▼]

This paper summarizes a study that was undertaken to reveal potential challenges and opportunities for integrating optimisation tools in Net/Nearly Zero Energy Buildings (NZEB) Design. The paper reviews current trends in simulation-based Building Performance Optimisation (BPO) and outlines major criteria for optimisation tools selection and evaluation. This is based on analyzing users’ needs for tools capabilities and requirement specifications. The review is carried out by means of interviews with 28 optimisation experts. The findings are based on an inter-group comparison between experts. The aim is to assess the gaps and needs for integrating BPO tools in NZEB Design. The findings indicate existing limitations including model uncertainty, computation time, difficulty of implementation and steep learning curve. Future directions anticipated or needed for improvement of current tools are presented. [less ▲]

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See detailComputational Prediction of Regulatory Networks linked to Secondary Metabolite Production
Rigali, Sébastien ULg

Scientific conference (2015, September)

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See detailA computational solid and fluid mechanical analysis of CAD-versus micro-CT-based models of regular Ti6Al4V scaffolds for bone tissue engineering
Truscello, Silvia; Kerckhofs, Greet ULg; Moesen, Maarten et al

in Histology and Histopathology (2011)

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See detailComputational Study Of Colipase Interaction With Lipid Droplets And Bile Salt Micelles
Kerfelec, Brigitte; Allouche, Maya; Colin, Damien et al

in Proteins-Structure Function and Bioinformatics (2008), 73(4), 828-38

Colipase is a key element in the lipase-catalyzed hydrolysis of dietary lipids. Although devoid of enzymatic activity, colipase promotes the pancreatic lipase activity in physiological intestinal ... [more ▼]

Colipase is a key element in the lipase-catalyzed hydrolysis of dietary lipids. Although devoid of enzymatic activity, colipase promotes the pancreatic lipase activity in physiological intestinal conditions by anchoring the enzyme at the surface of lipid droplets. Analysis of structures of NMR colipase models and simulations of their interactions with various lipid aggregates, lipid droplet, and bile salt micelle, were carried out to determine and to map the lipid binding sites on colipase. We show that the micelle and the oil droplet bind to the same side of colipase 3D structure, mainly the hydrophobic fingers. Moreover, it appears that, although colipase has a single direction of interaction with a lipid interface, it does not bind in a specific way but rather oscillates between different positions. Indeed, different NMR models of colipase insert different fragments of sequence in the interface, either simultaneously or independently. This supports the idea that colipase finger plasticity may be crucial to adapt the lipase activity to different lipid aggregates. [less ▲]

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See detailComputational Study Of Lipid-Destabilizing Protein Fragments: Towards A Comprehensive View Of Tilted Peptides
Lins, Laurence ULg; Charloteaux, Benoît ULg; Thomas, Annick ULg et al

in Proteins-Structure Function and Genetics (2001), 44(4), 435-47

Tilted peptides are short sequence fragments (10-20 residues long) that possess an asymmetric hydrophobicity gradient along their sequence when they are helical. Due to this gradient, they adopt a tilted ... [more ▼]

Tilted peptides are short sequence fragments (10-20 residues long) that possess an asymmetric hydrophobicity gradient along their sequence when they are helical. Due to this gradient, they adopt a tilted orientation towards a single lipid/water interface and destabilize the lipids. We have detected those peptides in many different proteins with various functions. While being all tilted-oriented at a single lipid/water interface, no consensus sequence can be evidenced. In order to better understand the relationships between their lipid-destabilizing activity and their properties, we used IMPALA to classify the tilted peptides. This method allows the study of interactions between a peptide and a modeled lipid bilayer using simple restraint functions designed to mimic some of the membrane properties. We predict that tilted peptides have access to a wide conformational space in membranes, in contrast to transmembrane and amphipathic helices. In agreement with previous studies, we suggest that those metastable configurations could lead to the perturbation of the acyl chains organization and could be a general mechanism for lipid destabilization. Our results further suggest that tilted peptides fall into two classes: those from proteins acting on membrane behave differently than destabilizing fragments from interfacial proteins. While the former have equal access to the two layers of the membrane, the latter are confined within a single lipid layer. This could be in relation with the organization of lipid substrate on which the peptides physiologically act. [less ▲]

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See detailComputational Study Of Nisin Interaction With Model Membrane
Lins, Laurence ULg; Ducarme, P.; Breukink, E. et al

in Biochimica et Biophysica Acta-Biomembranes (1999), 1420(1-2), 111-20

Nisin is a 34-residue lantibiotic widely used as food preservative. Its mode of action on the bacterial cytoplasmic membrane is unclear. It should form ion channels but a molecular description of the ... [more ▼]

Nisin is a 34-residue lantibiotic widely used as food preservative. Its mode of action on the bacterial cytoplasmic membrane is unclear. It should form ion channels but a molecular description of the interaction between nisin and phospholipids is lacking. The interactions between nisin and a membrane and the influence of phospholipids are here analysed by molecular modelling. The NMR structures of nisin in a micellar environment were previously determined (Van den Hooven et al., Eur. J. Biochem. 235 (1996) 382-393) Those structures were used to start with. They were refined by running a Monte Carlo procedure at a model lipid/water interface. It was shown that nisin is adsorbing onto the interface, with its N-terminal moiety more deeply inserted in lipids than the C-end, indicating distinct hydrophobic properties of the N- and C-domains. Therefore, we suggest that the N-terminal part is implied in the insertion of nisin in lipids, while the C-terminal moiety could be involved in the initial interaction with the membrane surface. Modelling the interaction of nisin with different neutral or anionic phospholipids shows that it disturbs the lipid organisation. The disturbance is maximal with phosphatidylglycerol. In this system, nisin curves the surface of phosphatidylglycerol layer round suggesting it could induce micelle formation. This could be a preliminary step to pore formation. It suggests that phosphatidylglycerol could have a direct action on nisin insertion and on ion channel formation. Appearance of a curvature also agrees with the 'wedge model' proposed in the literature for the nisin pore formation. [less ▲]

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See detailComputational study of the error distribution in right-censored and selection-biased regression models
Laurent, Géraldine ULg; Heuchenne, Cédric ULg

Conference (2010, May 18)

Consider the regression model Y = m(X) + σ(X) Ɛ where m(X) =E [Y|X] and σ²(X) = Var [Y|X] are unknown smooth functions and the error Ɛ, with unknown distribution, is independent of X. The pair (X,Y) is ... [more ▼]

Consider the regression model Y = m(X) + σ(X) Ɛ where m(X) =E [Y|X] and σ²(X) = Var [Y|X] are unknown smooth functions and the error Ɛ, with unknown distribution, is independent of X. The pair (X,Y) is subject to generalized selection bias and the response to right censoring. We construct a new estimator for the cumulative distribution function of the error Ɛ, and develop a bootstrap technique to select the smoothing parameter involved in the procedure. The estimator is studied via extended simulations and applied to real unemployment data. [less ▲]

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See detailComputational Surprisal Analysis Speeds-Up Genomic Characterization of Cancer Processes
Kravchenko-Balasha, N.; Simon, Simcha; Levine, R. D. et al

in Plos One (2014), 9(11), 108549

Detailed reference viewed: 12 (2 ULg)