Lou Chitkushev

MULTIPRED2: a computational system for large-scale identification of peptides predicted to bind to HLA supertypes and alleles.

Abstract MULTIPRED2 is a computational system for facile prediction of peptide binding to multiple alleles belonging to human leukocyte antigen (HLA) class I and class II DR molecules. It enables prediction of peptide binding to products of individual HLA alleles, combination of alleles, or HLA supertypes. NetMHCpan and NetMHCIIpan are used as prediction engines. The 13 HLA Class I supertypes are A1, A2, A3, A24, B7, B8, B27, B44, B58, B62, C1, and C4. The 13 HLA Class II DR supertypes are DR1, DR3, DR4, DR6, DR7, DR8, DR9, DR11, DR12, DR13, DR14, DR15, and DR16. In total, MULTIPRED2 enables prediction of peptide binding to 1077 variants representing 26 HLA supertypes. MULTIPRED2 has visualization modules for mapping promiscuous T-cell epitopes as well as those regions of high target concentration – referred to as T-cell epitope hotspots. Novel graphic representations are employed to display the predicted binding peptides and immunological hotspots in an intuitive manner and also to provide a global view of results as heat maps. Another function of MULTIPRED2, which has direct relevance to vaccine design, is the calculation of population coverage. Currently it calculates population coverage in five major groups in North America. MULTIPRED2 is an important tool to complement wet-lab experimental methods for identification of T-cell epitopes. It is available at http://cvc.dfci.harvard.edu/multipred2/.

HPVdb: a data mining system for knowledge discovery in human papillomavirus with applications in T cell immunology and vaccinology.

High-risk human papillomaviruses (HPVs) are the causes of many cancers, including cervical, anal, vulvar, vaginal, penile and oropharyngeal. To facilitate diagnosis, prognosis and characterization of these cancers, it is necessary to make full use of the immunological data on HPV available through publications, technical reports and databases. These data vary in granularity, quality and complexity. The extraction of knowledge from the vast amount of immunological data using data mining techniques remains a challenging task. To support integration of data and knowledge in virology and vaccinology, we developed a framework called KB-builder to streamline the development and deployment of web-accessible immunological knowledge systems. The framework consists of seven major functional modules, each facilitating a specific aspect of the knowledgebase construction process. Using KB-builder, we constructed the Human Papillomavirus T cell Antigen Database (HPVdb). It contains 2781 curated antigen entries of antigenic proteins derived from 18 genotypes of high-risk HPV and 18 genotypes of low-risk HPV. The HPVdb also catalogs 191 verified T cell epitopes and 45 verified human leukocyte antigen (HLA) ligands. Primary amino acid sequences of HPV antigens were collected and annotated from the UniProtKB. T cell epitopes and HLA ligands were collected from data mining of scientific literature and databases. The data were subject to extensive quality control (redundancy elimination, error detection and vocabulary consolidation). A set of computational tools for an in-depth analysis, such as sequence comparison using BLAST search, multiple alignments of antigens, classification of HPV types based on cancer risk, T cell epitope/HLA ligand visualization, T cell epitope/HLA ligand conservation analysis and sequence variability analysis, has been integrated within the HPVdb. Predicted Class I and Class II HLA binding peptides for 15 common HLA alleles are included in this database as putative targets. HPVdb is a knowledge-based system that integrates curated data and information with tailored analysis tools to facilitate data mining for HPV vaccinology and immunology. To our best knowledge, HPVdb is a unique data source providing a comprehensive list of HPV antigens and peptides. Database URL: http://cvc.dfci.harvard.edu/hpv/

Big Data Analytics in Immunology: A Knowledge-Based Approach

With the vast amount of immunological data available, immunology research is entering the big data era. These data vary in granularity, quality, and complexity and are stored in various formats, including publications, technical reports, and databases. The challenge is to make the transition from data to actionable knowledge and wisdom and bridge the knowledge gap and application gap. We report a knowledge-based approach based on a framework called KB-builder that facilitates data mining by enabling fast development and deployment of web-accessible immunological data knowledge warehouses. Immunological knowledge discovery relies heavily on both the availability of accurate, up-to-date, and well-organized data and the proper analytics tools. We propose the use of knowledge-based approaches by developing knowledgebases combining well-annotated data with specialized analytical tools and integrating them into analytical workflow. A set of well-defined workflow types with rich summarization and visualization capacity facilitates the transformation from data to critical information and knowledge. By using KB-builder, we enabled streamlining of normally time-consuming processes of database development. The knowledgebases built using KB-builder will speed up rational vaccine design by providing accurate and well-annotated data coupled with tailored computational analysis tools and workflow.

Reducing the complexity of virtual machine networking

Virtualization is an enabling technology that improves scalability, reliability, and flexibility. Virtualized networking is tackled by emulating or paravirtualizing network interface cards. This approach, however, leads to complexities (implementation and management) and has to conform to some limitations imposed by the Ethernet standard. RINA turns the current approach to virtualized networking on its head: instead of emulating networks to perform inter-process communication on a single processing system, it sees networking as an extension to local inter-process communication. In this article, we show how RINA can leverage a paravirtualization approach to achieve a more manageable solution for virtualized networking. We also present experimental results performed on IRATI, the reference open source implementation of RINA, which shows the potential performance that can be achieved by deploying our solution.

Unreliable inter process communication in Ethernet: migrating to RINA with the shim DIF

There is often a requirement to interface a new model to a legacy implementation by creating a shim between them to make the legacy appear as close to the new model as possible. This is a common exercise, usually fraught with frustrations, but here we find the exercise reveals fundamental aspects about nature of layers that were previously not well understood. Here we will be primarily concerned with creating a shim between RINA and IEEE 802.1q (VLANs). The Recursive InterNet Architecture (RINA) proposes a network architecture derived from the fundamentals of InterProcess Communication (IPC). This yields a recursively layered architecture of Distributed IPC Facilities (DIFs).

HPVdb: a Data Mining System for Knowledge Discovery in Human Papillomavirus with Applications in T cell Immunology and Vaccinology

High-risk human papilloma viruses (HPV) are the causes of many cancers, including cervical, anal, vulvar, vaginal, penile and oropharyngeal. To facilitate diagnosis, prognosis, and characterization of these cancers, we constructed the Human Papillomavirus T cell Antigen Database (HPVdb). It contains 2865 curated antigen entries of antigenic proteins derived from 18 genotypes of high-risk HPV and 18 genotypes of low-risk HPV. HPVdb also catalogs 96 verified T cell epitopes and 45 verified HLA ligands. Primary amino acid sequences of HPV antigens were collected and annotated from UniProtKB. T cell epitopes and HLA ligands were collected from data mining of scientific literature. The data were subject to extensive quality control (redundancy elimination, error detection, and vocabulary consolidation). A set of computational tools for in-depth analysis, such as sequence comparison using BLAST search, multiple alignments of antigens, classification of HPV types based on cancer risk, and T cell epitope/HLA ligand visualization, have been integrated in HPVdb. Predicted Class I and Class II HLA binding peptides for 15 common HLA alleles are included in this database as putative targets. HPVdb is a specialized database that integrates curated data and information with tailored analysis tools to facilitate data mining to aid rational vaccine design by discovery of vaccine targets. To our best knowledge, HPVdb is a unique data source providing a comprehensive list of antigen peptides in HPV. It is available at http://cvc.dfci.harvard.edu/hpv/ and http://met-hilab.bu.edu/hpvdb/.

From protecting protocols to layers: Designing, implementing and experimenting with security policies in RINA

Current Internet security is complex, expensive and ineffective. The usual argument is that the TCP/IP protocol suite was not designed having security in mind and security mechanisms have been added as add-ons or separate protocols. We argue that fundamental limitations in the Internet architecture are a major factor contributing to the insecurity of the Net. In this paper we explore the security properties of the Recursive InterNetwork Architecture, analyzing the principles that make RINA networks inherently more secure than TCP/IP-based ones. We perform the specification, implementation and experimental evaluation of the first authentication and SDU protection policies for RINA networks. RINAs approach to securing layers instead of protocols increases the security of networks, while reducing the complexity and cost of providing security.

Identities, Anonymity and Information Warfare

We discuss the primarily role of anonymity and identity manipulation in information warfare. We contend that those who engage in information warfare have very similar goals as those involved in cyber-crime and cyber-terrorism. Today Internet-based commerce has become global, representing a significant component of the world market. Network-based personal communications services are rapidly becoming the method of choice for many nations. In fact many critical infrastructure components are managed and controlled remotely. Yet these various capabilities are usurped by cyber-warriors, terrorists, or other criminals.

Biomarkers in Immunology: from Concepts to Applications

In this paper, we summarized the challenges and promises of the study of immune biomarkers. We reviewed key concepts in biomarker discovery and discussed the framework for applying these concepts in the study of the immune system and its effects on the disease -- cancer, infection, allergy, immunodeficiencies, and autoimmunity. The immune system plays a special role in biomarker discovery since it interacts with all other systems in the human body and immune biomarkers are relevant for large number of diseases.

Seamless network renumbering in RINA: Automate address changes without breaking flows!

Network renumbering in the IP world is a complicated and expensive procedure that has to be carefully planned and executed to avoid routing, security (firewall, ACLs) and transport connection integrity problems. The source of most of these issues is in the lack of a complete naming and addressing architecture in the TCP/IP protocol suite. This paper analyses the issues related to IP networks renumbering, identifying its root causes. Then it looks into how these issues affect renumbering in networks based on RINA, a network architecture with a complete naming scheme. Theoretical analysis backed up by experimentation results indicate that renumbering in RINA networks not only is seamless (can be done without impacting existing flows) but also does not require any special mechanisms.