Hardware software co-design of the Aho-Corasick algorithm: Scalable for protein identification?

Pattern matching is commonly required in many application areas and bioinformatics is a major area of interest that requires both exact and approximate pattern matching. Much work has been done in this area, yet there is still a significant space for improvement in efficiency, flexibility, and throughput. This paper presents a hardware software co-design of Aho-Corasick algorithm in Nios II soft-processor and a study on its scalability for a pattern matching application. A software only approach is used to compare the throughput and the scalability of the hardware software co-design approach. According to the results we obtained, we conclude that the hardware software co-design implementation shows a maximum of 10 times speed up for pattern size of 1200 peptides compared to the software only implementation. The results also show that the hardware software co-design approach scales well for increasing data size compared to the software only approach

Hardware accelerated protein inference framework

Protein inference plays a vital role in the proteomics study. Two major approaches could be used to handle the problem of protein inference; top-down and bottom-up. This paper presents a framework for protein inference, which uses hardware accelerated protein inference framework for handling the most important step in a bottom-up approach, viz. peptide identification during the assembling process. In our framework, identified peptides and their probabilities are used to predict the most suitable reference protein cluster for a given input amino acid sequence with the probability of identified peptides. The framework is developed on an FPGA where hardware software co-design techniques are used to accelerate the computationally intensive parts of the protein inference process. In the paper we have measured, compared and reported the time taken for the protein inference process in our framework against a pure software implementation

EVIDENCE UPDATING IN A HETEROGElNEOUS SENSOR ENVIRONMENT

ABSTRACT Nodes in a distributed sensor network (DSN) gather and fuse information generated by heterogeneous sources to arrive at local decisions targeted at achieving a given global mission objective. These sources typically possess very diverse scopes of 'expertise' or frames of discernment (FoDs) that renders updating a knowledge base from the evidence received a challenging task. In this paper, we present a Dempster-Shafer (DS) theory based evidence updating strategy that accommodates such non-identical FoDs. It is composed of a linear combination of the available evidence and incoming evidence conditioned to the source it is being generated from. The linear combination weights can be used to accommodate differences in source reliability and 'inertia' of the existing knowledge base. Strategies to choose these weights are also proposed

Distributed evidence filtering: the recursive case

A novel approach named recursive evidence filtering for information processing in distributed sensor networks (DSNs) is presented. It is based on the Dempster-Shafer (DS) formalism, facilitating evidence exchange and fusion in a simple and straightforward manner, while accommodating for partial and incomplete information. Certain restrictions on the coefficients impose several challenges in the design of such evidence filters suggesting that arbitrary frequency shaping is not possible. A general design procedure for IIR type evidence filters is presented with example

Genetic polymorphisms associated with anti-malarial antibody levels in a low and unstable malaria transmission area in southern Sri Lanka

ABSTRACT: BACKGROUND: The incidence of malaria in Sri Lanka has significantly declined in recent years. Similar trends were seen in Kataragama, a known malaria endemic location within the southern province of the country, over the past five years. This is a descriptive study of anti-malarial antibody levels and selected host genetic mutations in residents of Kataragama, under low malaria transmission conditions. METHODS: Sera were collected from 1,011 individuals residing in Kataragama and anti-malarial antibodies and total IgE levels were measured by a standardized ELISA technique. Host DNA was extracted and used for genotyping of selected SNPs in known genes associated with malaria. The antibody levels were analysed in relation to the past history of malaria (during past 10 years), age, sex, the location of residence within Kataragama and selected host genetic markers. RESULTS: A significant increase in antibodies against Plasmodium falciparum antigens AMA1, MSP2, NANP and Plasmodium vivax antigen MSP1 in individuals with past history of malaria were observed when compared to those who did not. A marked increase of anti-MSP1(Pf) and anti-AMA1(Pv) was also evident in individuals between 45-59 years (when compared to other age groups). Allele frequencies for two SNPs in genes that code for IL-13 and TRIM-5 were found to be significantly different between those who have experienced one or more malaria attacks within past 10 years and those who did not. When antibody levels were classified into a low-high binary trait, significant associations were found with four SNPs for anti-AMA1(Pf); two SNPs for anti-MSP1(Pf); eight SNPs for anti-NANP(Pf); three SNPs for anti-AMA1(Pv); seven SNPs for anti-MSP1(Pv); and nine SNPs for total IgE. Eleven of these SNPs with significant associations with anti-malarial antibody levels were found to be non- synonymous. CONCLUSIONS: Evidence is suggestive of an age-acquired immunity in this study population in spite of low malaria transmission levels. Several SNPs were in linkage disequilibrium and had a significant association with elevated antibody levels, suggesting that these host genetic mutations might have an individual or collective effect on inducing or/and maintaining high anti-malarial antibody levels

Evidence updating in a heterogeneous sensor environment DIGITAL SIGNAL PROCESSING-COMPUTER AIDED NETWORK DESIGN-ADVANCED TECHNOLOGY

Nodes in a distributed sensor network (DSN) gather and fuse information generated by heterogeneous sources to arrive at local decisions targeted at achieving a given global mission objective. These sources typically possess very diverse scopes of 'expertise' or frames of discernment (FoDs) that renders updating a knowledge base from the evidence received a challenging task. In this paper, we present a Dempster-Shafer (DS) theory based evidence updating strategy that accommodates such non-identical FoDs. It is composed of a linear combination of the available evidence and incoming evidence conditioned to the source it is being generated from. The linear combination weights can be used to accommodate differences in source reliability and 'inertia' of the existing knowledge base. Strategies to choose these weights are also proposed

Host genetic polymorphisms and serological response against malaria in a selected population in Sri Lanka

Background: Antibodies against the merozoite surface protein 1-19 (MSP1-19) and the apical membrane antigen 1 (AMA1) of the malaria parasite (Plasmodium vivax) are proven to be important in protection against clinical disease. Diferences in the production/maintenance of antibodies may be due to many factors including host genetics. This paper discusses the association of 4 anti-malarial antibodies with selected host genetic markers.Methods: Blood was collected from individuals (n=242) with a history of malaria within past 15 years for DNA and serum. ELISA was carried out for serum to determine the concentration of anti-malarial antibodies MSP1-19 and AMA1 for both vivax and falciparum malaria. 170 SNPs related to malaria were genotyped. Associations between seropositivity, antibody levels and genetic, non-genetic factors were determined.Results: Age ranged 13–74 years (mean age=40.21 years). Majority were females. Over 90% individuals possessed either one or more type(s) of anti-malarial antibodies. Five SNPs were signifcantly associated with seropositivity. One SNP was associated with MSP1-19_Pv(rs739718); 4 SNPs with MSP1-19_Pf (rs6874639, rs2706379, rs2706381 and rs2075820) and1 with AMA1_Pv (rs2075820). Eleven and 7 genotypes (out of 15) were signifcantly associated with either presence or absence of antibodies. Three SNPs were found to be signifcantly associated with the antibody levels viz. rs17411697 with MSP1-19_Pv, rs2227491 with AMA1_Pv and rs229587 with AMA1_Pf. Linkage of the markers in the two groups was similar, but lower LOD scores were observed in seropositives compared to seronegatives.Discussion and conclusions: The study suggests that several SNPs in the human genome that exist in Sri Lankan populations are signifcantly associated with anti-malarial antibodies, either with generation and/or maintenance of antibodies for longer periods, which can be due to either individual polymorphisms or most probably a combined efect of the markers