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2021

Quality by design tools reducing the gap from bench to bedside for nanomedicine

doi:10.1016/j.ejpb.2021.10.005

Bayesian Augmented Clinical Trials in TB Therapeutic Vaccination

doi:10.3389/fmedt.2021.719380

A multi-step and multi-scale bioinformatic protocol to investigate potential SARS-CoV-2 vaccine targets

doi:10.1093/bib/bbab403

PEAK: A Clever Python Tool for Exploratory, Regression, and Classification Data. A Case Study for COVID-19

doi:10.1007/978-3-030-88163-4_31

Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility

doi:10.1002/psp4.12669

Possible Contexts of Use for In Silico trials methodologies: a consensus-based review

doi:10.1109/JBHI.2021.3090469

Verification of an agent-based disease model of human Mycobacterium tuberculosis infection

doi:10.1002/cnm.3470

How can we accelerate COVID-19 vaccine discovery?

doi:10.1080/17460441.2021.1935861

In silico trials: Verification, validation and uncertainty quantification of predictive models used in the regulatory evaluation of biomedical products.

doi:10.1016/j.ymeth.2020.01.011

2020

Immune-checkpoint inhibitors from cancer to COVID‑19: A promising avenue for the treatment of patients with COVID‑19 (Review)

doi:10.3892/ijo.2020.5159

In silico trial to test COVID-19 candidate vaccines: a case study with UISS platform.

doi:10.1186/s12859-020-03872-0

Computational modeling of the immune response in multiple sclerosis using epimod framework.

doi:10.1186/s12859-020-03823-9

Moving forward through the in silico modeling of tuberculosis: a further step with UISS-TB.

doi:10.1186/s12859-020-03762-5

Generation of digital patients for the simulation of tuberculosis with UISS-TB.

doi:10.1186/s12859-020-03776-z

Toward computational modelling on immune system function.

doi:10.1186/ s12859-020-03897-5

PETAL: a python tool for deep analysis of biological pathways.

doi:10.1093/bioinformatics/btaa1032

Evaluation of the predictive capability of petal tool: a retrospective study on potential tyrosine kinases drug resistance targets.

doi:10.1109/BIBM49941.2020.9312986

Modeling, simulation and prediction of protein structures for the design of oncolytic viruses.

doi:10.1109/ BIBM49941.2020.9313198

Verify: a toolbox for deterministic verification of computational models.

doi:10.1109/ BIBM49941.2020.9313312

In silico evaluation of daclizumab and vitamin d effects in multiple sclerosis using agent based models.

doi:10.1007/978-3-030-63061-4_25

Multiple sclerosis disease: A computational approach for investigating its drug interactions.

doi:10.1007/978-3-030-63061-4_26

Efficient and settings-free calibration of detailed kinetic metabolic models with enzyme isoforms characterization.

doi:10.1007/978-3-030-34585-3_17

The combination of artificial intelligence and systems biology for intelligent vaccine design

doi:10.1080/17460441.2020.1791076

The Potential of Computational Modeling to Predict Disease Course and Treatment Response in Patients with Relapsing Multiple Sclerosis.

doi:10.3390/cells9030586

Gene silencing of transferrin-1 receptor as a potential therapeutic target for human follicular and anaplastic thyroid cancer.

doi:10.1016/j.omto.2020.01.003

POSITION PAPER: Credibility of In Silico Trial Technologies - A Theoretical Framing.

doi:10.1109/JBHI.2019.2949888

2019

Toward computational modelling on immune system function.

doi:10.1186/s12859-019-3239-x

Predicting the artificial immunity induced by RUTI® vaccine against tuberculosis using universal immune system simulator (UISS)

doi:10.1186/s12859-019-3045-5

Parallelisation strategies for agent based simulation of immune systems.

doi:10.1186/s12859-019-3181-y

A computational approach based on the colored Petri net formalism for studying multiple sclerosis.

doi:10.1186/s12859-019-3196-4

MAP3K8 as mediator of resistance to vemurafenib in thyroid cancer stem cells.

doi:10.1093/bioinformatics/bty969

EpiMethEx: a tool for large-scale integrated analysis in methylation hotspots linked to genetic regulation.

doi:10.1186/s12859-018-2397-6

Design and optimization of PEGylated nanoparticles intended for Berberine Chloride delivery.

doi:10.1016/j.jddst.2019.05.012

(2S)-N-2-methoxy-2-phenylethyl-6,7-benzomorphan compound (2S-LP2): Discovery of a biased mu/delta opioid receptor agonist

doi:10.1016/j.ejmech.2019.02.043

Evaluation of the efficacy of RUTI and ID93/GLA-SE vaccines in tuberculosis treatment: in silico trial through UISS-TB simulator.

doi:10.1109/BIBM47256.2019.8983060

Generation of digital patients for the simulation of tuberculosis with UISS-TB.

doi:10.1109/BIBM47256.2019.8983100

A MapReduce tool for in-depth analysis of KEGG pathways: identification and visualization of therapeutic target candidates.

doi:10.1109/BIBM47256.2019.8982978

Exploiting Stochastic Petri Net formalism to capture the Relapsing Remitting Multiple Sclerosis variability under Daclizumab administration.

doi:10.1109/BIBM47256.2019.8983368

Gene expression and pathway bioinformatics analysis detect a potential predictive value of MAP3K8 in thyroid cancer progression.

doi:10.1109/BIBM47256.2019.8983036

A MapReduce based tool for the analysis and discovery of novel therapeutic targets.

doi:10.1109/EMPDP.2019.8671609

2018

Computational modeling of brain pathologies: the case of multiple sclerosis.

doi:10.1093/bib/bbw123

Computational modeling reveals MAP3K8 as mediator of resistance to vemurafenib in thyroid cancer stem cells.

doi:10.1093/bioinformatics/bty969

In silico clinical trials: concepts and early adoptions.

doi:10.1093/bib/bby043

GPU Accelerated Analysis of Treg-Teff Cross Regulation in Relapsing-Remitting Multiple Sclerosis.

doi:10.1007/978-3-030-10549-5_49

Agent based modeling of relapsing multiple sclerosis: a possible approach to predict treatment outcome.

doi:10.1109/BIBM.2018.8621109

Parallel Pair-Wise Interaction for Multi-Agent Immune Systems Modelling.

doi:10.1109/BIBM.2018.8621404

Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric Nets.

doi:10.1109/BIBM.2018.8621259

An agent based modeling approach for the analysis of tuberculosis - immune system dynamics.

doi:10.1109/BIBM.2018.8621355

BIOESOnet: A Tool for the Generation of Personalized Human Metabolic Pathways from 23andMe Exome Data

10.1007/978-3-319-95933-7_42

Combining Parallel Genetic Algorithms and Machine Learning to improve the research of optimal vaccination protocols.

doi:10.1109/PDP2018.2018.00070

DNA methylation and gene expression in melanoma: A large-scale integrated analysis.

doi:10.1158/1538-7445.AM2018-5305

Computational immunogenetics.

doi:10.1016/B978-0-12-809633-8.20452-4

2017

Combining agent based-models and virtual screening techniques to predict the best citrus-derived vaccine adjuvants against Human Papillomavirus.

doi:10.1186/s12859-017-1961-9

Continuous Petri Nets and microRNA analysis in melanoma.

doi:10.1109/TCBB.2017.2733529

Optimization and analisys of vaccination shedules using Simulated Annealing and Agent Based Models.

doi:10.1109/BIBM.2017.8217877

Introducing scale factor adjustments on agent-based simulations of the immune system.

doi:10.1109/BIBM.2017.8217878

2DIs: a SBML compliant web platform for the design and modeling of immune system interactions.

doi:10.1007/978-3-319-63312-1_13

Modeling PI3K/PDK1/Akt and MAPK Signaling Pathways using Continuous Petri Nets.

doi:10.1007/978-3-319-63312-1_15

2016

A methodological approach for using High-Level Petri Nets to model the adaptive immune system response.

doi:10.1186/s12859-016-1361-6

ODEs approaches in modeling fibrosis: Comment on ``Towards a unified approach in the modeling of fibrosis: A review with research perspectives`` by Martine Ben Amar and Carlo Bianca.

doi: 10.1016/j.plrev.2016.05.012

Agent based simulations in disease modeling Comment on ``Towards a unified approach in the modeling of fibrosis: A review with research perspectives'' by Martine Ben Amar and Carlo Bianca.

doi:10.1016/j.plrev.2016.05.006

A computational model to predict the immune system activation by citrus derived vaccine adjuvants.

doi:10.1093/bioinformatics/btw293

Formal analysis of the surgical pathway and development of a new software tool to assist surgeons in the decision making in primary breast surgery.

doi:10.1016/j.breast.2016.06.004

Computational modeling in melanoma for novel drug discovery.

doi:10.1080/17460441.2016.1174688

Computational Modeling of PI3K/AKT and MAPK Signaling Pathways in Melanoma Cancer.

doi:10.1371/journal.pone.0152104

SHyFTA, a Stochastic Hybrid Fault Tree Automaton for the modelling and simulation of Dynamic Reliability problems.

doi:10.1016/j.eswa.2015.10.046

2015

Advances in Computational Immunology.

doi:10.1155/2015/170920

Agent based modeling of the effects of potential treatments over the blood-brain barrier in multiple sclerosis.

doi:10.1016/j.jim.2015.08.014

Computational modeling of the expansion of human cord blood CD133+ hematopoietic stem/progenitor cells with different cytokine combinations.

doi:10.1093/bioinformatics/btv172

Computational modelling approaches to vaccinology.

doi:10.1016/j.phrs.2014.08.006

Targeting the minimum vertex set problem with an enhanced genetic algorithm improved with local search strategies.

doi:10.1007/978-3-319-22180-9_18

2014

Induction of T cell memory by a dendritic cell vaccine: a computational model.

doi:10.1093/bioinformatics/btu059

Computational and Bioinformatics Techniques for Immunology.

doi:10.1155/2014/263189

Modeling biology spanning different scales: An open challenge.

doi:10.1155/2014/902545

Agent based modeling of the immune system: NetLogo, a promising framework.

doi:10.1155/2014/907171

In silico modeling of the immune system: cellular and molecular scale approaches.

doi:10.1155/2014/371809

Relapsing-Remitting Multiple Scleroris and the role of Vitamin D: an agent based model.

doi:10.1145/2649387.2660844

OntoFast: Construct ontology rapidly.

doi:10.1007/978-3-319-11716-4_21

2013

Agent based modeling of Treg-Teff cross regulation in relapsing-remitting multiple sclerosis.

doi:10.1186/1471-2105-14-S16-S9

Mathematical modeling of biological systems.

doi:10.1093/bib/bbs061

Cancer vaccines: state of the art of the computational modeling approaches.

doi:10.1155/2013/106407

The dynamic-to-static conversion of Dynamic Fault Trees using Stochastic Dependency Graphs and Stochastic Activity Networks.

doi:10.4236/eng.2013.52016

Physio-Environmental Sensing and Live Modeling.

doi:10.2196/ijmr.2092

Computational Biology Modeling across Different Scales.

doi:10.5220/0004405706170625

Persistence analysis in a Kolmogorov-type model for cancer-immune system competition.

doi:10.1063/1.4825874

iAtheroSim: atherosclerosis process simulator on smart devices.

doi:10.1145/2506583.2512356

2012

Combining cellular automata and lattice Boltzmann method to model multiscale avascular tumor growth coupled with nutrient diffusion and immune competition.

doi:10.1016/j.jim.2011.11.009

A modeling framework for immune-related diseases.

doi:10.1051/mmnp/20127304

Mathematical and computational models in tumor immunology.

doi:10.1051/mmnp/20127312

Mathematical modeling of the immune system recognition to mammary carcinoma antigen.

doi:10.1186/1471-2105-13-S17-S21

Optimal vaccination schedule search using genetic algorithm over MPI technology.

doi:10.1186/1472-6947-12-129

Immune System Modeling and Related Pathologies.

doi:10.1155/2012/274702

Modeling cancer vaccines.

doi:10.1109/CISIS.2012.13

Computational models as novel tools for cancer vaccines.

2011

SimB16: Modeling induced immune system response against B16-melanoma.

doi:10.1371/journal.pone.0026523

Predicting long-term vaccine efficacy against metastases using agents.

doi:10.1007/978-3-642-24553-4_15

A model of cytotoxic t antitumor activation stimulated by pulsed dendritic cells.

doi:10.1063/1.3637840

Compartmental mathematical modeling of immune system - melanoma competition.

GRID Computing and Computational Immunology.

Sexual Risk Behavior for HIV and other sexual diseases in Burkina Faso and structure of a sexual contact network.

2010

Current issues in tumor immunology.

doi:10.2174/157489310792006684

Immunogrid: towards agent-based simulations of the human immune system at a natural scale.

doi:10.1098/rsta.2010.0067

In silico modeling and in vivo efficacy of cancer-preventive vaccinations.

doi:10.1158/0008-5472.CAN-10-0701

A novel paradigm for cell and molecule interaction ontology: From the CMM model to IMGT-ONTOLOGY.

doi:10.1186/1745-7580-6-1

Vaccine protocols optimization: In silico experiences.

doi:10.1016/j.biotechadv.2009.10.001

Modeling the competition between lung metastases and the immune system using agents.

doi:10.1186/1471-2105-11-S7-S13

GRIDUISS - A grid based universal immune system simulator framework.

doi:10.1007/978-3-642-14922-1_36

Cancer immunoprevention: what can we learn from in silico models?

doi:10.1007/978-3-642-14831-6_15

The immunogrid simulator: how to use it.

doi:10.1007/978-3-642-14571-1_1

Universal Immune System Simulator framework (UISS).

doi:10.1145/1854776.1854900

Modeling artificial immunity against mammary carcinoma.

2009

The MWF method for kinetic equations system.

doi:10.1016/j.camwa.2008.09.018

Effect of LDL-apheresis on plasma lipids, chitotriosidase and anti-oxLDL antibodies in heterozygous familial hypercholesterolemia.

doi:10.4236/jbise.2009.27072

Immunogrid, an integrative environment for large-scale simulation of the immune system for vaccine discovery, design and optimization.

doi:10.1093/bib/bbp014

Simulated annealing and optimal protocols.

doi:10.1142/S0218126609005770

Searching of optimal vaccination schedules.

doi:10.1109/MEMB.2009.932919

Agent based modeling of atherosclerosis: a concrete help in personalized treatments.

doi:10.1007/978-3-642-04020-7_41

Agent based modeling of lung metastasis-immune system competition.

doi:10.1007/978-3-642-03246-2_1

Toward multi-organs simulations of immune-pathogen interactions.

doi:10.1109/ISDA.2009.119

HAMFAST: Fast hamming distance computation.

doi:10.1109/CSIE.2009.223

Grid-based atherosclerosis simulations.

A biological optimization problem on the Grid.

P2SI2-ImmunoGrid services integration: a working example of web based approach.

Grid-based cancer growth simulations.

2008

Modeling immune system control of atherogenesis.

doi:10.1093/bioinformatics/btn306

Computational simulations of the immune system for personalized medicine: state of the art and challenges.

doi:10.2174/187569208786733839

Optimal vaccination schedules using simulated annealing.

doi:10.1093/bioinformatics/btn260

Agent based modeling of humoral response to atherogenesis.

Modelling Vaccine Protocols.

Predictive models in tumor immunology.

Translational immunomics of cancer immunoprevention.

2007

Optimization of HAART with genetic algorithms and agent-based models of HIV infection.

doi:10.1093/bioinformatics/btm408

Towards a personalized schedule with Triplex vaccine.

doi:10.1007/978-3-540-73400-0_79

A genetic algorithm for shortest path motion problem in three dimensions.

doi:10.1007/978-3-540-74205-0_58

Tumor associated antigen variation - in silico experiments using the Sicilian Grid.

2006

Discovery of cancer vaccination protocols with a genetic algorithm driving an agent based simulator.

doi:10.1186/1471-2105-7-352

Modeling tumor immunology.

doi:10.1142/S0218202506001479

Analysis of vaccine's schedules using models.

doi:10.1016/j.cellimm.2007.03.002

Model deconstruction of an immunoprevention vaccine.

doi:10.1007/11881223_43

Genetic algorithm against cancer.

doi:10.1007/11676935_27

The stabilization effect of the Triplex vaccine.

doi:10.1142/9789812774118_0083

2005

Modeling and simulation of cancer immunoprevention vaccine.

doi:10.1093/bioinformatics/bti426

Modelling vaccination schedules for a cancer immunoprevention vaccine.

doi:10.1186/1745-7580-1-5

Maths against cancer.

doi:10.1142/9789812835635_0129

Using viruses to improve GAs.

doi:10.1007/11539902_19

2004

MT-FWL: Multi-Target Firewall Language.

2003

An ant-algorithm for the weighted minimum hitting set problem.

doi:10.1109/SIS.2003.1202239

The hitting set problem and evolutionary algorithmic techniques with ad-hoc viruses (HEAT-V).

doi:10.1007/3-540-45110-2_29

2002

An evolutionary algorithm for the T-constrained variation of minimum hitting set problem.

doi:10.1109/CEC.2002.1006262

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