BACKGROUND: Advances in next-generation sequencing technologies have facilitated extensive analysis of B cell and T cell receptor (BCR/TCR, respectively) sequences from monoclonal hybridoma libraries, single B cells, and single T cells, generating vast amounts of important data pertaining to antigen recognition. However, existing workflows and bioinformatics tools often lack the flexibility and scalability needed to handle large clonal level datasets effectively. An initial system and hybridoma dependent version of this code was distributed as part of the NeuroMabSeq publication, but clonevdjseq aims to be a technical addendum for broader system compatibility and enhanced modeling. RESULTS: We present clonevdjseq, an integrated and accessible software solution leveraging nextflow and Django. Developed primarily for large hybridoma libraries, the workflow and pipeline is amenable to BCR/TCR sequence analysis of homogenous populations or clones of B and T cells, respectively. The clonevdjseq pipeline includes modules for read processing, amplicon denoising, and quality control of paired variable light/heavy chains of BCRs from B cells and hybridomas, or alpha(ɑ)/beta(β) and delta(δ)/gamma(γ) chains of TCRs in the case of T cell applications. The pipeline is built upon a robust, high-throughput library prep protocol, upon which processed data has been verified across thousands of monoclonal antibodies. The results of this effort has yielded sequences used to develop functional recombinant monoclonal antibodies and single chain variable fragments as a part of the NeuroMabSeq initiative where thousands of hybridoma samples were processed (Mitchell et al. in Sci Rep 13(1):16200, 2023) as well as provide additional modeling and extensibility to other modalities. The clonevdjseq software is accessible via Nextflow and also offers a database and web app as a final optional step in the processing for dissemination of results and data exploration. CONCLUSIONS: clonevdjseq offers a comprehensive and scalable solution for the processing and analysis of large monoclonal and oligoclonal VDJ datasets. Its modular design, dynamic pipeline, and robust database integration facilitate efficient data management and analysis. The platform is publicly available and aims to support the research community by providing an accessible and flexible tool for archiving and dissemination of BCR sequences from hybridomas, with applicability for other applications such as TCR sequences from single-cell T cell populations.

Estimating cell type composition of blood and tissue samples is a biological challenge relevant in both laboratory studies and clinical care. In recent years, a number of computational tools have been developed to estimate cell type abundance using gene expression data. Although these tools use a variety of approaches, they all leverage expression profiles from purified cell types to evaluate the cell type composition within samples. In this study, we compare 12 cell type quantification tools and evaluate their performance while using each of 10 separate reference profiles. Specifically, we have run each tool on over 4000 samples with known cell type proportions, spanning both immune and stromal cell types. A total of 12 of these represent in vitro synthetic mixtures and 300 represent in silico synthetic mixtures prepared using single-cell data. A final 3728 clinical samples have been collected from the Framingham cohort, for which cell populations have been quantified using electrical impedance cell counting. When tools are applied to the Framingham dataset, the tool Estimating the Proportions of Immune and Cancer cells (EPIC) produces the highest correlation, whereas Gene Expression Deconvolution Interactive Tool (GEDIT) produces the lowest error. The best tool for other datasets is varied, but CIBERSORT and GEDIT most consistently produce accurate results. We find that optimal reference depends on the tool used, and report suggested references to be used with each tool. Most tools return results within minutes, but on large datasets runtimes for CIBERSORT can exceed hours or even days. We conclude that deconvolution methods are capable of returning high-quality results, but that proper reference selection is critical.

Peer-to-Peer (P2P) technologies provide efficient and low-cost delivery for commercial and user-generated content. Although a number of audio-visual content distribution services have been developed using P2P-based mechanisms, it is still a challenge to guarantee satisfactory user experience on high quality video streaming services due to the dynamic nature of P2P distribution. An objective assessment service is the key enabler of service quality monitoring and management. However, this complex task can not be achieved by any individual objective model that only captures a certain aspect of service quality. This paper introduces a multimodal quality evaluation framework that is specifically designed and implemented for the assessment of video streaming services in P2P-based IPTV systems. Results of initial experiments show the effectiveness of this framework.

This paper provides a summary and overview of the ACM workshop on advanced video streaming techniques for peer-to-peer networks and social networking.

In this paper we describe our experiences of developing and monitoring an Internet Television (IPTV) service in order to determine to what extent the system can provide useful hints (or triggers) that are exploitable by Content Distribution Networks (CDNs). Uniquely, our system integrates with social networking services and builds on the social graph to help form an understanding of user behaviour and potentially socially-motivated trends. By combining these attributes we are able to represent a social user journey for each user of the system which we seek to exploit for identifying potential trigger conditions. The paper concludes with an initial analysis of data collected during a five month trial of the service with staff and students of our University.

This paper describes a prototype application which enables the real-time monitoring and visualization of large Wide Area Networks (WANs) using smartphone devices. The techniques employed allow field engineers to rapidly gain access to a large information repository through the use of a camera equipped mobile phone. More specifically, the use of visual codes [11] attached to networking hardware and infrastructure cabling enables the real-time visualization of network traffic and statistics to be triggered by the capturing of images from a personal device. Moreover, the location and orientation of the phone are used as contextual parameters in order to control the specific information to be retrieved. The prototype described in this paper is currently under evaluation by Information Systems Services (ISS) which is responsible for network support across Lancaster University, the student residences network and also a large regional WAN spanning the whole of the North West of England. Our aim was to establish whether or not this user interaction technique could be harnessed for a real world application that would benefit field engineers who are responsible for maintaining a live production network interconnecting tens of thousands of hosts.

In this paper, we describe our experiences of developing and evaluating GUIDE, an intelligent electronic tourist guide. The GUIDE system has been built to overcome many of the limitations of the traditional information and navigation tools available to city visitors. For example, group-based tours are inherently inflexible with fixed starting times and fixed durations and (like most guidebooks) are constrained by the need to satisfy the interests of the majority rather than the specific interests of individuals. Following a period of requirements capture, involving experts in the field of tourism, we developed and installed a system for use by visitors to Lancaster. The system combines mobile computing technologies with a wireless infrastructure to present city visitors with information tailored to both their personal and environmental contexts. In this paper we present an evaluation of GUIDE, focusing on the quality of the visitor's experience when using the system.

The GUIDE system has been developed to provide city visitors with a hand-held context-aware tourist guide. The system has been successfully deployed in a major tourist destination and is currently at the stage where it is publicly available to visitors who wish to explore the city. Reaching this stage has been the culmination of a number of distinct research efforts. In more detail, the development of GUIDE has involved: capturing a real set of application requirements, investigating the properties of a cell-based wireless communications technology in a built-up environment and deploying a network based on this technology around the city, designing and populating an information model to represent attractions and key buildings within the city, prototyping the development of a distributed application running across portable GUIDE units and stationary cell-servers and finally, evaluating the entire system during an extensive field-trial study. This paper reports on our results in each of these areas. We believe that through our work on the GUIDE project we have produced a blueprint for the development of interactive context-aware systems that should be of real value to those in the community who wish to develop such systems in a practical environment.