MOTIVATION: Peptide mass fingerprinting (PMF) is a method for protein identification in which a protein is fragmented by a defined cleavage protocol (usually proteolysis with trypsin), and the masses of these products constitute a 'fingerprint' that can be searched against theoretical fingerprints of all known proteins. In the first stage of PMF, the raw mass spectrometric data are processed to generate a peptide mass list. In the second stage this protein fingerprint is used to search a database of known proteins for the best protein match. Although current software solutions can typically deliver a match in a relatively short time, a system that can find a match in real time could change the way in which PMF is deployed and presented. In a paper published earlier we presented a hardware design of a raw mass spectra processor that, when implemented in Field Programmable Gate Array (FPGA) hardware, achieves almost 170-fold speed gain relative to a conventional software implementation running on a dual processor server. In this article we present a complementary hardware realization of a parallel database search engine that, when running on a Xilinx Virtex 2 FPGA at 100 MHz, delivers 1800-fold speed-up compared with an equivalent C software routine, running on a 3.06 GHz Xeon workstation. The inherent scalability of the design means that processing speed can be multiplied by deploying the design on multiple FPGAs. The database search processor and the mass spectra processor, running on a reconfigurable computing platform, provide a complete real-time PMF protein identification solution.

MOTIVATION: High-resolution mass spectrometers generate large data files that are complex, noisy and require extensive processing to extract the optimal data from raw spectra. This processing is readily achieved in software and is often embedded in manufacturers' instrument control and data processing environments. However, the speed of this data processing is such that it is usually performed off-line, post data acquisition. We have been exploring strategies that would allow real-time advanced processing of mass spectrometric data, making use of the reconfigurable computing paradigm, which exploits the flexibility and versatility of Field Programmable Gate Arrays (FPGAs). This approach has emerged as a powerful solution for speeding up time-critical algorithms. We describe here a reconfigurable computing solution for processing raw mass spectrometric data generated by MALDI-ToF instruments. The hardware-implemented algorithms for de-noising, baseline correction, peak identification and deisotoping, running on a Xilinx Virtex 2 FPGA at 180 MHz, generate a mass fingerprint over 100 times faster than an equivalent algorithm written in C, running on a Dual 3 GHz Xeon workstation.

UNLABELLED: I describe a simple standalone program that assists in the preparation of peptide digestion maps. These are useful for comparative studies and for locating peptides within a primary sequence. The program creates an output file as scalable vector graphics that can then be viewed in a web browser or imported into a graphics-editing program. AVAILABILITY: The program, as a standalone executable, is available upon request from the author. CONTACT: [email protected].

This paper describes a stack for the Apple Macintosh Hypercard environment that facilitates the calculation of a set of thermodynamically-corrected pH buffers. Presented in the familiar Macintosh mouse-based environment, the program allows comprehensive buffer design and gives the user full control of buffer species, temperature, ionic strength, pH and choice of counter-ion to maintain the ionic strength at a fixed value. Addition of new buffers to the stack is straightforward and the recipes that are generated, including the weights of the various components, can be displayed on the screen or saved to a disk file for subsequent printing.

Computing in the biological sciences a survey Get access Robert J. Beynon Robert J. Beynon Department of Biochemistry, University of LiverpoolPO Box 147, Liverpool L69 3BX, UK Search for other works by this author on: Oxford Academic PubMed Google Scholar Bioinformatics, Volume 1, Issue 1, January 1985, Pages 7–9, https://doi.org/10.1093/bioinformatics/1.1.7 Published: 01 January 1985

Software for non-linear curve fitting has been written in BASIC to execute on the British Broadcasting Corporation Microcomputer. The program uses the direct search algorithm Pattern-search, a robust algorithm that has the additional advantage of needing specification of the function without inclusion of the partial derivatives. Although less efficient than gradient methods, the program can be readily configured to solve low-dimensional optimization problems that are normally encountered in life sciences. In writing the software, emphasis has been placed upon the 'user interface' and making the most efficient use of the facilities provided by the minimal configuration of this system.