BIOsigma

BIOsigma is a package of services devoted to:

  1. Design of Experiments:

    1. Screening of factors​

    2. Analysis of Effects

    3. Optimization of Response

    4. Robustness of Response

    5. Sample Size Determination

  2. Analysis of Data:

    1. Statistical Testing​

    2. Factorial Analysis

    3. Clustering Analysis 

    4. Analysis of Variance

    5. Regression Studies

    6. Classification Studies

    7. Spectral Analysis

    8. Signal Processing

    9. Dynamic System Identification

References:

[1] P. Guyot, E.-H. Djermoune, B. Chenuel, and T. Bastogne, “A signal demodulation based-method for the early detection of Cheyne-Stokes breathing in patients with severe heart failure,” Accepted in PLoS ONE, 2020.
[2] L. Batista, T. Bastogne, A. Delaunois, J.-P. Valentin, and F. Atienzar, “A statistical signal processing method to rank drug effects in cardiomyocyte impedance assays.,” Biomedical Signal Processing and Control, vol. 45, pp. 202–212, 2018.
[3] G. Vogin, T. Bastogne, L. Bodgi, J. Gillet-Daubin, A. Canet, S. Pereira, and N. Foray, “The pATM Immunofluorescence assay: a high-performance radiosensitivity assay to predict post radiotherapy over- reactions.,” International Journal of Radiation Oncology - Biology - Physics, vol. 101, no. 3, pp. 1–8, 2018.
[4] T. Bastogne, J.-L. Marchand, S. Pinel, and P. Vallois, “A branching process model of heterogeneous DNA damages caused by radiotherapy in in vitro cell cultures,” Mathematical Biosciences, 2017.
[5] P. Retif, T. Bastogne, and M. Barberi-Heyob, “Robustness analysis of a Geant4-Gate simulator for nano-radiosensitizers characterization,” IEEE Transactions on NanoBioscience, vol. 15, no. 3, pp. 209–217, 2016.
[6] P. Retif, A. Reinhard, P. Héna, V. Jouan-Hureaux, A. Chateau, L. Sancey, M. Barberi-Heyob, S. Pinel, and T. Bastogne, “Monte Carlo simulations guided by imaging to predict the in vitro ranking of radiosensitizing nanoparticles,” International Journal of Nanomedicine, 2016.
[7] M. Toussaint, S. Pinel, F. Auger, N. Durieux, M. Thomassin, E. Thomas, A. Moussaron, D. Meng, F. Plénat, M. Amouroux, T. Bastogne, C. Frochot, O. Tillement, F. Lux, and M. Barberi-Heyob, “Proton MR Spectroscopy and Diffusion MR Imaging Monitoring to Predict Tumor Response to Interstitial Photodynamic Therapy for Glioblastoma,” Theranostics, 2016.
[8] J.-B. Tylcz, T. T. Bastogne, A. Bourguignon, C. Frochot, and M. Barberi-Heyob, “Realtime tracking of the Photobleaching Trajectory during Photodynamic Therapy,” IEEE Transactions on Biomedical Engineering, 2016.
[9] J.-B. Tylcz, K. El Alaoui-Lasmaili, E.-H. Djermoune, N. Thomas, B. Faivre, and T. Bastogne, “Data-driven modeling and characterization of anti-angiogenic molecule effects on tumoral vascular density,” Biomedical Signal Processing and Control, vol. 20, pp. 52–60, July 2015.
[10] J.-B. Tylcz, T. Bastogne, H. Benachour, D. Bechet, E. Bullinger, H. Garnier, and M. Barberi-Heyob, “A Model-based Pharmacokinetics Characterization Method of Engineered Nanoparticles for Pilot Studies,” IEEE Transactions on NanoBioscience, pp. Volume:PP , Issue: 99, Apr. 2015.
[11] T. Bastogne, Thierry and P. Vallois, “An Extension of the Target Theory in Biology Applied to System Reliability,” in Models and Methods in Economics and Management Science: Essays in Honor of Charles S. Tapiero (F. E. Ouardighi and K. Kogan, eds.), International Series in Operations Research & Management Science, pp. 155–181, Springer, 2014.
[12] T. Baumuratova, S. Dobre, T. Bastogne, and T. Sauter, “Switch of sensitivity dynamics revealed with DyGloSA toolbox for dynamical global sensitivity analysis as an early warning for system’s critical transition,” PLoS ONE, vol. 8, p. e82973, Dec. 2013.
[13] H. Benachour, T. Bastogne, M. Toussaint, Y. Chemli, A. Sève, C. Frochot, F. Lux, O. Tillement, R. Vanderesse, and M. Barberi-Heyob, “Real-time monitoring of photocytotoxicity in nanoparticles- based photodynamic therapy: a model-based approach,” PLoS ONE, vol. 7, p. e48617, Nov. 2012.
[14] R. Keinj, T. Bastogne, and P. Vallois, “Tumor growth modeling based on cell and tumor lifespans,” Journal of Theoretical Biology, vol. 312, pp. 76–86, Nov. 2012.
[15] H. Benachour, A. Sève, T. Bastogne, C. Frochot, R. Vanderesse, J. Jasniewski, I. Miladi, C. Billotey, O. Tillement, F. Lux, and M. Barberi-Heyob, “Multifunctional peptide-conjugated hybrid silica nanoparticles for photodynamic therapy and MRI,” Theranostics, vol. 2, pp. 889–904, Sept. 2012.
[16] R. Keinj, T. Bastogne, and P. Vallois, “Multinomial model-based formulations of TCP and NTCP for radiotherapy treatment planning,” Journal of Theoretical Biology, vol. 279, pp. 55–62, June 2011.
[17] V. Morosini, T. Bastogne, C. Frochot, R. Schneider, A. François, F. Guillemin, and M. Barberi-Heyob, “Quantum Dot-folic acid conjugates as potential photosensitizers in photodynamic therapy of cancer,” Photochemical and Photobiological Sciences, vol. 10, pp. 842–851, May 2011.
[18] T. Bastogne, A. Samson, P. Vallois, S. Wantz-Mézières, S. Pinel, D. Bechet, and M. Barberi-Heyob, “Phenomenological modeling of tumor diameter growth based on a mixed effects model,” Journal of Theoretical Biology, vol. 262, pp. 544–552, 2010.
[19] D. Bechet, L. Tirand, B. Faivre, F. Plénat, C. Bonnet, T. Bastogne, C. Frochot, F. Guillemin, and M. Barberi Heyob, “Neuropilin-1 targeting photosensitization-induced early stages of thrombosis via tissue factor release,” Pharmaceutical Research / Pharmaceutical Research (Dordrecht), vol. 27, no. 3, pp. 468–479, 2010.
[20] L. Tirand, T. Bastogne, D. Bechet, M. Linder, N. Thomas, C. Frochot, F. Guillemin, and M. Barberi- Heyob, “Response surface methodology: an extensive potential to optimize photodynamic therapy conditions in vivo,” International Journal of Radiation Oncology, Biology, Physics, vol. 75, no. 1, pp. 244–252, 2009.
[21] J. Gravier, R. Schneider, C. Frochot, T. Bastogne, F. Schmitt, J. Didelon, F. Guillemin, and M. Barberi-Heyob, “Improvement of m-THPC-like photosensitizer selectivity with folate-based targeted delivery. Synthesis and in vivo selective delivery study,” Journal of Medicinal Chemistry, vol. 51, pp. 3867–3877, June 2008.
[22] T. Bastogne, S. Mézières-Wantz, N. Ramdani, P. Vallois, L. Tirand, D. Bechet, and M. Barberi-Heyob, “Parameter estimation of pharmacokinetics models in the presence of random timing errors,” European Journal of Control, vol. 14, no. 2, 2008.