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Editorial Advances in Computational Immunology Hindawi Publishing Corporation Journal of Immunology Research Volume 2015, Article ID 170920, 3 pages http://dx.doi.org/10.1155/2015/170920 Editorial Advances in Computational Immunology Francesco Pappalardo,1 Vladimir Brusic,2 Marzio Pennisi,3 and Guanglan Zhang4 1 Department of Drug Sciences, University of Catania, 95100 Catania, Italy 2Nazarbayev University, Astana 010000, Kazakhstan 3Department of Mathematics and Computer Science, University of Catania, 95100 Catania, Italy 4Boston University, Boston, MA 02201-2021, USA Correspondence should be addressed to Francesco Pappalardo; [email protected] Received 13 December 2015; Accepted 13 December 2015 Copyright © 2015 Francesco Pappalardo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Computational immunology and immunological bioinfor- potential is to use a panel of multidisease antibodies that can matics are firm and quickly growing research fields. Whereas be instrumental to know what the infectious agents are in the former aims to develop mathematical and/or computa- circulationinagivenpopulationandtheirputativedynamics. tional methods to study the dynamics of cellular and molec- This idea has not been tested in practice, but definitely ular entities during the immune response [1–4], the latter will require the extension of classical mathematical models focuses on proposing methods to investigate big genomic to fully account the immunological interaction between and proteomic immunological-related datasets and predict different diseases. new knowledge mainly by statistical inference and machine In their paper W. Schreiner and colleagues illustrate that learning algorithms. molecular dynamics was used to simulate large molecules of The glut of data produced by high-throughput instru- the immune system (major histocompatibility complexes, T- mentation, notably genomics, transcriptomics, epigenetics, cell receptors, and coreceptors). To characterize the relative and proteomics methods, requires computational tools for orientation and movements of domains local coordinate acquisition, storage, and analysis of immunological data. systems (based on principal component analysis) were gen- The exploitation of such a huge amount of immunological erated and directional cosines and Euler angles computed. data usually requires its conversion into computational prob- As a most interesting result, they found that the presence of lems, their solution using mathematical and computational the coreceptor seems to influence the dynamics within the approaches, and then the translation of the obtained results protein complex, in particular the relative movements of the into immunologically meaningful interpretations. two -helices, G1andG2. In this special issue, we take an interest from mathemati- It is assessed that the application of personalized medicine cians, bioinformaticians, computational scientists, and engi- requires integration of different data to determine each neers together with experimental immunologists to present patient’s unique clinical constitution. The automated analysis and discuss latest developments in different subareas of com- ofmedicaldataisagrowingfieldwheredifferentmachine putational immunology, ranging from databases applications learning techniques are used to minimize the time consuming to computational vaccine design, modelling, and simulation task of manual analysis. and their application to basic and clinical immunology. In the paper contributed by C.-M. Svensson et al., the The review from N. Sepulveda´ et al. calls attention to authors investigate the interobserver variability of image data serology data in conjunction with mathematical modelling comprising fluorescently stained circulating tumor cells and in providing a powerful approach to inform on malaria its effect on the performance of two automated classifiers, transmission intensity and putative changes over time. Their a random forest and a support vector machine. They found conclusions show that an interesting idea with public health that uncertainty in annotation between observers limited 2 Journal of Immunology Research the performance of the automated classifiers, especially when Thereareatpresentfewtoolsavailabletoassistwiththe it was included in the test set on which classifier performance determination and analysis of B-cell lineage trees from next- was measured. generation sequencing data. The paper from W. D Lees and Therapeutic protein products (TPP) have been widely A. J. Shepherd presents two utilities that support automated used to treat a variety of human diseases, including cancer, large-scale analysis and the creation of publication-quality hemophilia, and autoimmune diseases. However, TPP can results. The tools are available on the web and are also induce unwanted immune responses that can impact both available for download so that they can be integrated into an drugefficacyandpatientsafety.Thepresenceofaggregates automated pipeline. These utilities can be used with any suit- isofparticularconcernastheyhavebeenimplicatedin able phylogenetic inference method and with any antibody inducing both T-cell independent and T-cell dependent germline library and hence are species-independent. immune responses. L. Yin and collaborators used mathe- Vaccination is historically one of the most important matical modelling to evaluate several mechanisms through medical interventions for the prevention of infectious disease. which aggregates of TPP could contribute to the development Previously, vaccines were typically made of rather crude mix- of immunogenicity. Their computational analyses suggest tures of inactivated or attenuated causative agents. However, that aggregates are unlikely to induce T-cell independent over the last 10–20 years, several important technological and antibody responses through BCR cross-linking. In contrast, computational advances have enabled major progress in the aggregates could contribute to immunogenicity via the T- discovery and design of potently immunogenic recombinant cell dependent pathway by inducing the presentation of high protein vaccine antigens. L. Liljeroos and colleagues discuss affinity epitopes that may not be present in nonaggregated three key breakthrough approaches that have potentiated TPP and/or by enhancing danger signal to maturate dendritic structural and computational vaccine design. They illustrate cells and activate T-cells. the growing power of combining sequencing, structural, A. K. Irin et al. investigate computational modelling and computational approaches and discuss how this may approaches on epigenetic factors in neurodegenerative and drive the design of novel immunogens suitable for future autoimmune diseases and their mechanistic analysis. The vaccines urgently needed to increase the global prevention of authors examine the major milestones in epigenetics research infectious disease. in the context of diseases and various computational MIrExpress is a new database which takes advantage of approaches developed in the last decades to unravel new the information theory, as well as the Pearson linear corre- epigenetic modifications. However, there are limited studies lation method, to measure the linear correlation, nonlinear that systematically link genetic and epigenetic alterations correlation, and their hybrid of cell-specific gene coexpres- of DNA to the aetiology of diseases, they said. In this sions in immune cells. In the work from J. Wang et al., work,A.K.Irinandcoauthorsshowhowdisease-related the authors describe this database that totally includes 16 epigenetic knowledge can be systematically captured and human cell groups, involving 20,283 human genes. The integrated with heterogeneous information into a functional expression data and the calculated correlation results from context using Biological Expression Language (BEL). This the database are interactively accessible on the web page novel methodology, based on BEL, enables the integration and can be implemented for other related applications and of epigenetic modifications such as DNA methylation or researches. acetylationofhistonesintoaspecificdiseasenetwork. Publicallyavailableinfluenzadataareavaluableresource In the paper by G. Bocharov et al., the authors show how for computational analyses with applications in vaccine the modelling approaches can be implemented to address design. Similarly, existing bioinformatics tools provide the diverse aspects of immune system functioning under normal means for extraction of information and new knowledge. conditions and in response to LCMV and, importantly, However, to utilize the full potential of these resources, data make quantitative predictions of the outcomes of immune preprocessing must be performed and analytical tools must system perturbations. This may highlight that data-driven be carefully combined into well-defined workflows. C. Simon applications of meaningful mathematical models in infection et al. describe FluKB, a knowledge-based system focusing biology remain a challenge. on data and analytical tools for influenza vaccine discovery. MHC -helices form the antigen-binding cleft and are of The main goal of FluKB is to provide access to curated particular interest for immunological reactions. To monitor influenza sequence and epitope data and enhance the analysis these helices in molecular dynamics simulations, the paper
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