164,022 research outputs found
De Novo Assembly of Nucleotide Sequences in a Compressed Feature Space
Sequencing technologies allow for an in-depth analysis
of biological species but the size of the generated datasets
introduce a number of analytical challenges. Recently, we
demonstrated the application of numerical sequence representations
and data transformations for the alignment of short
reads to a reference genome. Here, we expand out approach
for de novo assembly of short reads. Our results demonstrate
that highly compressed data can encapsulate the signal suffi-
ciently to accurately assemble reads to big contigs or complete
genomes
A Reference-Free Algorithm for Computational Normalization of Shotgun Sequencing Data
Deep shotgun sequencing and analysis of genomes, transcriptomes, amplified
single-cell genomes, and metagenomes has enabled investigation of a wide range
of organisms and ecosystems. However, sampling variation in short-read data
sets and high sequencing error rates of modern sequencers present many new
computational challenges in data interpretation. These challenges have led to
the development of new classes of mapping tools and {\em de novo} assemblers.
These algorithms are challenged by the continued improvement in sequencing
throughput. We here describe digital normalization, a single-pass computational
algorithm that systematizes coverage in shotgun sequencing data sets, thereby
decreasing sampling variation, discarding redundant data, and removing the
majority of errors. Digital normalization substantially reduces the size of
shotgun data sets and decreases the memory and time requirements for {\em de
novo} sequence assembly, all without significantly impacting content of the
generated contigs. We apply digital normalization to the assembly of microbial
genomic data, amplified single-cell genomic data, and transcriptomic data. Our
implementation is freely available for use and modification
SLIQ: Simple Linear Inequalities for Efficient Contig Scaffolding
Scaffolding is an important subproblem in "de novo" genome assembly in which
mate pair data are used to construct a linear sequence of contigs separated by
gaps. Here we present SLIQ, a set of simple linear inequalities derived from
the geometry of contigs on the line that can be used to predict the relative
positions and orientations of contigs from individual mate pair reads and thus
produce a contig digraph. The SLIQ inequalities can also filter out unreliable
mate pairs and can be used as a preprocessing step for any scaffolding
algorithm. We tested the SLIQ inequalities on five real data sets ranging in
complexity from simple bacterial genomes to complex mammalian genomes and
compared the results to the majority voting procedure used by many other
scaffolding algorithms. SLIQ predicted the relative positions and orientations
of the contigs with high accuracy in all cases and gave more accurate position
predictions than majority voting for complex genomes, in particular the human
genome. Finally, we present a simple scaffolding algorithm that produces linear
scaffolds given a contig digraph. We show that our algorithm is very efficient
compared to other scaffolding algorithms while maintaining high accuracy in
predicting both contig positions and orientations for real data sets.Comment: 16 pages, 6 figures, 7 table
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Generation of Micro Mechanical Devices Using Stereo Lithography
A high resolution machining setup for creating three-dimensional precision components from a
UV-curable photo-resin has been developed. By using frequency-converted diode-pumped solid
state lasers, functional micro-mechanical devices are directly fabricated in a successive layer-bylayer fashion. Within this paper, the direct generation of micro assemblies having
moving components without further assembly of parts will be presented. The micro system
design is based on user-defined 3D-CAD data and will completively be built up within the
fabrication cycle. By using specially developed μSL materials with suitable properties for micromechanical parts, the development from Rapid Prototyping towards Rapid Production of small
series is intended.Mechanical Engineerin
Developments in the tools and methodologies of synthetic biology.
Synthetic biology is principally concerned with the rational design and engineering of biologically based parts, devices, or systems. However, biological systems are generally complex and unpredictable, and are therefore, intrinsically difficult to engineer. In order to address these fundamental challenges, synthetic biology is aiming to unify a body of knowledge from several foundational scientific fields, within the context of a set of engineering principles. This shift in perspective is enabling synthetic biologists to address complexity, such that robust biological systems can be designed, assembled, and tested as part of a biological design cycle. The design cycle takes a forward-design approach in which a biological system is specified, modeled, analyzed, assembled, and its functionality tested. At each stage of the design cycle, an expanding repertoire of tools is being developed. In this review, we highlight several of these tools in terms of their applications and benefits to the synthetic biology community
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