BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

Motivation: Counting the number of occurrences of every k-mer (substring of length k) in a long string is a central subproblem in many applications, including genome assembly, error correction of sequencing reads, fast multiple sequence alignment and repeat detection. Recently, the deep sequence coverage generated by next-generation sequencing technologies has caused the amount of sequence to be processed during a genome project to grow rapidly, and has rendered current k-mer counting tools too slow and memory intensive. At the same time, large multicore computers have become commonplace in research facilities allowing for a new parallel computational paradigm.

Results: We propose a new k-mer counting algorithm and associated implementation, called Jellyfish, which is fast and memory efficient. It is based on a multithreaded, lock-free hash table optimized for counting k-mers up to 31 bases in length. Due to their flexibility, suffix arrays have been the data structure of choice for solving many string problems. For the task of k-mer counting, important in many biological applications, Jellyfish offers a much faster and more memory-efficient solution.

Availability: The Jellyfish software is written in C++ and is GPL licensed. It is available for download at http://www.cbcb.umd.edu/software/jellyfish.

Contact: [email protected]

Supplementary information:Supplementary data are available at Bioinformatics online.

/pdf/a-fast-lock-free-approach-for-efficient-parallel-counting-of-3tjx1nqa3f.pdf

A fast, lock-free approach for efficient parallel counting of occurrences of k-mers

Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

Integrative Genomics Viewer

Hypertension 66 (20.3%) 24 (24.2%) 30 (16.3%) NS Diabetes 20 (6.2%) 7 (7.1%) 10 (5.4%) NS Excess weight 78 (24%) 27 (27.3%) 44 (23.9%) NS Smokers 64 (19.7%) 17 (17.2%) 35 (19.0%) NS Age >50 years 137 (42.2%) 54 (54.5%) 67 (36.4%) <0.02 Kidney disease 7 (2.2%) 1 (1%) 5 (2.7%) NS Family history, DM 102 (31.4%) 28 (28.3%) 66 (35.9%) NS

Conflict of interest statement. None declared.

https://www.cell.com/cancer-cell/pdf/S1535-6108(14)00037-3.pdf

Mutant p53 in Cancer: New Functions and Therapeutic Opportunities

Understanding the structure and function of DNA sequences represents an important area of research in modern biology. One of the interesting structures occurring in DNA is a palindrome. Biologists believe that palindromes play an important role in regulation of gene activity and other cell processes because they are often observed near promoters, introns and specific untranslated regions. Unfortunately, the time complexity of algorithms for palindrome detection increases when mutations in the form of character insertions, deletions or substitutions are taken into consideration. In recent years, several works have been aimed at acceleration of such algorithms using dedicated circuits capable of potentially large-scale searching. However, widespread use of such circuits is often complicated by varying user task details or the need to use a specific target platform. The objective of this work is therefore to create a model of hardware architecture for approximate palindrome detection and develop a technique for automatic mapping of this model to the target platform without intervention of an experienced designer. The proposed model and the mapping technique are implemented and evaluated on a family of chips with Virtex5 technology.

Architecture model for approximate palindrome detection

Hardware accelerators for approximate string matching play an important role in an increasing number of modern bioinformatic applications They are able to reduce the task complexity from quadratic to linear and show a speed up in orders of hundreds when compared with the respective software implementation However, their wider use is limited by the lack of flexibility and modularity required by often variable tasks In this respect, it is desirable to develop a procedure for automatic design and implementation of such accelerators, to reach high performance and efficiency typical for strongly optimized architectures, with as little human effort on the side of the designer as possible This paper proposes the essential element of such a procedure, a method for the calculation of generic hardware architecture parameters The proposed method is evaluated on a range of typical approximate string matching tasks It demonstrates the differences in the designed architecture, when performance of individual tasks is maximized

Automatic generation of circuits for approximate string matching

Systolic array architectures for approximate string matching play a significant role as hardware accelerators in biological applications. However, their wider use is limited by the lack of flexibility required by often variable tasks. In this respect, it is desirable to develop a procedure for automatic design and implementation of such accelerators to reach high performance and efficiency with as little human effort on the side of the designer as possible. This paper proposes the essential element of such procedure, a method for the calculation of generic systolic array parameters with respect to maximal performance and efficient resource utilization

A flexible technique for the automatic design of approximate string matching architectures

We report the latest details on improvements made or planned
for the VPCR simulation software currently accessible on the
Internet. We describe the inner workings of the dynamic
amplification simulation model, concentrating mostly on the
time- and sensitivity-critical step of sequence matching.
Replacement of BLAST by the more sensitive and faster PRMEX
similarity search program resulted in a marked improvement of
PCR product predictions. Further speed improvements were
acheived using hardware acceleration of approximate sequence
matching.

/pdf/genomic-pcr-simulation-with-hardware-accelerated-3ortml5jo8.pdf

Genomic PCR simulation with hardware-accelerated approximatesequence matching

Genome-wide association studies have become a standard way of discovering novel causative alleles by looking for statisticaly significant associations in patient genotyping data. The present challenge for these methods is to discover associations involving multiple interacting loci, a common phenomenon in diseases often related to epistasis. The main problem is the exponential increase in necessary computational power for every additional interacting locus considered in association tests. Several approaches have been proposed to manage this problem, including limiting analysis to interacting pairs and filtering SNPs according to external biological knowledge. Here we explore the possibilities of using public protein interaction data and pathway maps to filter out only pairs of SNPs that are likely to interact, perhaps because of epistatic mechanisms working at the protein level. After filtering all possible pairs of SNPs by their presence in common protein-protein interactions or proteins sharing a metabolic or signalling pathway, we calculate the possible reduction in computational requirements under different scenarios. We discuss these exploratory results in the context of the so-called "lost heredity" and the usefulness of this approach for similar scenarios.

Matej Lexa

Papers

Architecture model for approximate palindrome detection

Automatic generation of circuits for approximate string matching

A flexible technique for the automatic design of approximate string matching architectures

Genomic PCR simulation with hardware-accelerated approximatesequence matching

The Possibilities of Filtering Pairs of SNPs in GWAS Studies - Exploratory Study on Public Protein-interaction and Pathway Data