Computer aided selection of candidate vaccine antigens

Immunoinformatics is an emergent branch of informatics science that long ago pullulated from the tree of knowledge that is bioinformatics. It is a discipline which applies informatic techniques to problems of the immune system. To a great extent, immunoinformatics is typified by epitope prediction methods. It has found disappointingly limited use in the design and discovery of new vaccines, which is an area where proper computational support is generally lacking. Most extant vaccines are not based around isolated epitopes but rather correspond to chemically-treated or attenuated whole pathogens or correspond to individual proteins extract from whole pathogens or correspond to complex carbohydrate. In this chapter we attempt to review what progress there has been in an as-yet-underexplored area of immunoinformatics: the computational discovery of whole protein antigens. The effective development of antigen prediction methods would significantly reduce the laboratory resource required to identify pathogenic proteins as candidate subunit vaccines. We begin our review by placing antigen prediction firmly into context, exploring the role of reverse vaccinology in the design and discovery of vaccines. We also highlight several competing yet ultimately complementary methodological approaches: sub-cellular location prediction, identifying antigens using sequence similarity, and the use of sophisticated statistical approaches for predicting the probability of antigen characteristics. We end by exploring how a systems immunomics approach to the prediction of immunogenicity would prove helpful in the prediction of antigens.     

Computer aided analysis for biosensing and screening

Biosensors with animal and microbial cells immobilized close to the tip of a membrane electrode have been developed for chemical and drug testing. Our experimental results show that biosensors can be used for drug screening and to provide useful information about various cell-chemical interactions. A computer aided analysis (CAA) software package is being developed here using the biosensor for various screening purposes. This software package enables us to use a computer to analyze the biosensor dynamic responses. Computer simulation and parameter estimation techniques are used to select the best model and to describe the biochemical and pharmacologic effects of various chemicals and drugs on different cell lines.     

Computer aided fluorescence imaging of photosynthetic systems

A fluorescence video imaging system utilizing relatively inexpensive commercial components is described. The instrument utilizes a black and white CCD video camera detector, a commercial video imaging board and a IBM-AT compatible computer. The color output of the imaging board greatly aids in the users ability to visually discriminate areas of interest in the video field. Software development that enables the user to capture kinetic traces in real time from the video images is also described. The system is used to monitor fluorescence from photosynthetic systems. The usefulness of the system in screening for photosynthetic mutants is also demonstrated. The cost of the system can be kept below $12,000.Abbreviations CCD charge-coupled device - DCMU diuron, 3-[3,4-Dichlorophenyl]1,1-dimethylurea - AGC automatic gain control - LUT look-up table - AOI area of interest - CPU central processing unit - RAM random access memory - ADC analog-to-digital converter - FVIPS fluorescence video image processing software - I/O input/output - F₀ dark-level fluorescence - OIDPSMT characteristic transient components, where O is dark level, I is intermediary peak, D is dip, P is peak of fast transient, S is quasi-steady state level, M is second maximum, T is terminal level