Efficient Error Correction Research Articles

SpeedyGenes: an improved gene synthesis method for the efficient production of error-corrected, synthetic protein libraries for directed evolution.

The de novo synthesis of genes is becoming increasingly common in synthetic biology studies. However, the inherent error rate (introduced by errors incurred during oligonucleotide synthesis) limits its use in synthesising protein libraries to only short genes. Here we introduce SpeedyGenes, a PCR-based method for the synthesis of diverse protein libraries that includes an error-correction procedure, enabling the efficient synthesis of large genes for use directly in functional screening. First, we demonstrate an accurate gene synthesis method by synthesising and directly screening (without pre-selection) a 747 bp gene for green fluorescent protein (yielding 85% fluorescent colonies) and a larger 1518 bp gene (a monoamine oxidase, producing 76% colonies with full catalytic activity, a 4-fold improvement over previous methods). Secondly, we show that SpeedyGenes can accommodate multiple and combinatorial variant sequences while maintaining efficient enzymatic error correction, which is particularly crucial for larger genes. In its first application for directed evolution, we demonstrate the use of SpeedyGenes in the synthesis and screening of large libraries of MAO-N variants. Using this method, libraries are synthesised, transformed and screened within 3 days. Importantly, as each mutation we introduce is controlled by the oligonucleotide sequence, SpeedyGenes enables the synthesis of large, diverse, yet controlled variant sequences for the purposes of directed evolution.

Trowel: a fast and accurate error correction module for Illumina sequencing reads

The ability to accurately read the order of nucleotides in DNA and RNA is fundamental for modern biology. Errors in next-generation sequencing can lead to many artifacts, from erroneous genome assemblies to mistaken inferences about RNA editing. Uneven coverage in datasets also contributes to false corrections. We introduce Trowel, a massively parallelized and highly efficient error correction module for Illumina read data. Trowel both corrects erroneous base calls and boosts base qualities based on the k-mer spectrum. With high-quality k-mers and relevant base information, Trowel achieves high accuracy for different short read sequencing applications.The latency in the data path has been significantly reduced because of efficient data access and data structures. In performance evaluations, Trowel was highly competitive with other tools regardless of coverage, genome size read length and fragment size. Trowel is written in C++ and is provided under the General Public License v3.0 (GPLv3). It is available at http://trowel-ec.sourceforge.net. euncheon.lim@tue.mpg.de or weigel@tue.mpg.de Supplementary data are available at Bioinformatics online.

Bandwidth efficient adaptive forward error correction mechanism with feedback channel

Multimedia content is very sensitive to packet loss and therefore multimedia streams are typically protected against packet loss, either by supporting retransmission requests or by adding redundant forward error correction (FEC) data. However, the redundant FEC information introduces significant additional bandwidth requirements, as compared to the bitrate of the original video stream. Especially on wireless and mobile networks, bandwidth availability is limited and variable. In this article, an adaptive FEC (A-FEC) system is presented whereby the redundancy rate is dynamically adjusted to the packet loss, based on feedback messages from the client. We present a statistical model of our A-FEC system and validate the proposed system under different packet loss conditions and loss probabilities. The experimental results show that 57-95% bandwidth gain can be achieved compared with a static FEC approach.

Efficient error correction for N-particle polarized entangled states distribution over the collective-noise channel exploiting time entanglement

We propose an efficient error correction protocol for N-particle polarization entanglement states distribution over the collective-noise channel.The time entanglement is exploited in our protocol for its stability in noisy environment. The protocol is deterministic and the successful probability is 100 %. Moreover, the setup is just composed of linear optical elements, which are feasible with existing experimental technology. Therefore, the quantum resources can be saved and the protocol can be easily realized in experiments. With all the advantages above, our protocol could be useful in remote quantum communication.

A Nanomechanical Fredkin Gate

Irreversible logic operations inevitably discard information, setting fundamental limitations on the flexibility and the efficiency of modern computation. To circumvent the limit imposed by the von Neumann-Landauer (VNL) principle, an important objective is the development of reversible logic gates, as proposed by Fredkin, Toffoli, Wilczek, Feynman, and others. Here, we present a novel nanomechanical logic architecture for implementing a Fredkin gate, a universal logic gate from which any reversible computation can be built. In addition to verifying the truth table, we demonstrate operation of the device as an AND, OR, NOT, and FANOUT gate. Excluding losses due to resonator dissipation and transduction, which will require significant improvement in order to minimize the overall energy cost, our device requires an energy of order 10(4) kT per logic operation, similar in magnitude to state-of-the-art transistor-based technologies. Ultimately, reversible nanomechanical logic gates could play a crucial role in developing highly efficient reversible computers, with implications for efficient error correction and quantum computing.

Comparison of parallelization strategies for min-sum decoding of irregular LDPC codes

Low-Density Parity-Check (LDPC) codes are powerful error correcting codes. LDPC decoders have been implemented as efficient error correction codes on dedicated VLSI hardware architectures in recent years. This paper describes two strategies to parallelize min-sum decoding of irregular LDPC codes. The first implements min-sum LDPC decoders on multicore platforms using OpenMP, while the other uses the Compute Unified Device Architecture (CUDA) to parallelize LDPC decoding on Graphics Processing Units (GPUs). Empirical studies on data with various scales show that the performance of these decoding processes is improved by these parallel strategies and the GPUs provide more efficient, fast implementation decoder.

Energy Efficient Coded Communication for IEEE 802.15.4 Compliant Wireless Sensor Networks

The multipath nature of the wireless environment does not provide reliable links for robust communication in wireless senor networks (WSNs). These unreliable links increase the error level to a greater extent and therefore, reduces battery life. Hence, there arises a need for developing energy efficient forward error correction code that avoids more energy consuming Automatic Repeat request (ARQ) scheme used in WSNs to improve link reliability. In this paper, we consider a simple block error correction codes such as cyclic and Bose Chaudhuri Hocquenghem (BCH) codes to be used in IEEE 802.15.4 RF transceiver based sensor nodes. The simulations are performed to measure network parameters such as bit error rate, and energy spent per bit under Rayleigh fading channel environment. It is found that BCH code with code rate of 0.8 provides coding gain of 1.6 dB when compared with cyclic and ARQ schemes and proves to be an energy efficient code among the codes considered.

Cyclin A regulates kinetochore microtubules to promote faithful chromosome segregation

The most conspicuous event in the cell cycle is the alignment of chromosomes in metaphase. Chromosome alignment fosters faithful segregation through the formation of bi-oriented attachments of kinetochores to spindle microtubules. Strikingly, numerous kinetochore-microtubule (k-MT) attachment errors are present in early mitosis (prometaphase)1, and the persistence of those errors is the leading cause of chromosome mis-segregation in aneuploid human tumor cells that continually mis-segregate whole chromosomes (e.g. chromosomal instability)2–7. How robust error correction is achieved in prometaphase to ensure error-free mitosis remains unknown. Here we show that k-MT attachments in prometaphase cells are significantly less stable than in metaphase cells. The switch to more stable k-MT attachments in metaphase requires the proteasome-dependent destruction of cyclin A in prometaphase. Persistent cyclin A expression prevents k-MT stabilization even in cells with aligned chromosomes. In contrast, k-MTs are prematurely stabilized in cyclin A-deficient cells. Consequently, cells lacking cyclin A display higher rates of chromosome mis-segregation. Thus, the stability of k-MT attachments increases decisively in a coordinated fashion among all chromosomes as cells transit from prometaphase to metaphase. Cyclin A creates a cellular environment that promotes microtubule detachment from kinetochores in prometaphase to ensure efficient error correction and faithful chromosome segregation.

RACER: Rapid and accurate correction of errors in reads

High-throughput next-generation sequencing technologies enable increasingly fast and affordable sequencing of genomes and transcriptomes, with a broad range of applications. The quality of the sequencing data is crucial for all applications. A significant portion of the data produced contains errors, and ever more efficient error correction programs are needed. We propose RACER (Rapid and Accurate Correction of Errors in Reads), a new software program for correcting errors in sequencing data. RACER has better error-correcting performance than existing programs, is faster and requires less memory. To support our claims, we performed extensive comparison with the existing leading programs on a variety of real datasets. RACER is freely available for non-commercial use at www.csd.uwo.ca/∼ilie/RACER/.

High Threshold Error Correction for the Surface Code

An algorithm is presented for error correction in the surface code quantum memory. This is shown to correct depolarizing noise up to a threshold error rate of 18.5%, exceeding previous results and coming close to the upper bound of 18.9%. The time complexity of the algorithm is found to be polynomial with error suppression, allowing efficient error correction for codes of realistic sizes.

부호화된 MIMO 시스템에서 QR 분해를 이용한 효율적인 연판정 검출

무선통신시스템에서의 고용량 데이터 전송을 위해 MIMO 전송은 필수적인 기술의 하나로 자리매김하였다. 더불어 열악한 채널환경에서 요구되는 성능을 만족하기 위해서는 반드시 고효율 오류정정부호를 사용하여야하며, 반복적인 복호 기법을 사용하는 터보부호나 저밀도 패리티 검사부호 등이 그 예라고 할 수 있다. 이러한 오류정정 부호들의 우수한 성능은 반드시 MIMO 검출 단에서의 정확한 연판정 검출 값이 전제되어야 한다. 본 논문에서는 매우 적은 복잡도로 효과적으로 연판정 검출 값을 복호기에 전달 할 수 있는 방법으로써 채널 행렬의 QR 분해기법을 적용한 연판정 검출 기법을 제안한다. 본 논문에서 제안하는 방식은 먼저 연판정 MIMO 검출 단계를 두 단계로 나누어 복잡도를 획기적으로 감소시킬 수 있는 방법과 결합하였으며, 채널 행렬에 대하여 직접 역행렬을 구하는 방식에 비해서 안테나 수가 증가할수록 훨씬 더 적은 복잡도로 동일한 성능을 얻을 수 있다. Multi-Input Multi-Output (MIMO) transmission is now considered as one of essential techniques enabling high rate data transmissions in wireless communication systems. In addition, severe channel impairments in wireless systems should be compensated by using highly efficient forward error correction (FEC) codes. Turbo codes or low density parity check (LDPC) codes, using iterative decoding with soft decision detection information (SDDI), are the most common examples. The excellent performance of these codes should be conditioned on accurate estimation of SDDI from the MIMO detection process. In this paper, we propose a soft MIMO detection scheme using QR decomposition of channel matrices as an efficient means to provide accurate SDDI to the iterative decoder. The proposed method employed a two sequential soft MIMO detection process in order to reduce computational complexity. Compared to the soft ZF method calculating the direct inverse of the channel matrix, the complexity of the proposed method can be further reduced as the number of antennas is increased, without any performance degradation.

Efficient error correction for next-generation sequencing of viral amplicons

BackgroundNext-generation sequencing allows the analysis of an unprecedented number of viral sequence variants from infected patients, presenting a novel opportunity for understanding virus evolution, drug resistance and immune escape. However, sequencing in bulk is error prone. Thus, the generated data require error identification and correction. Most error-correction methods to date are not optimized for amplicon analysis and assume that the error rate is randomly distributed. Recent quality assessment of amplicon sequences obtained using 454-sequencing showed that the error rate is strongly linked to the presence and size of homopolymers, position in the sequence and length of the amplicon. All these parameters are strongly sequence specific and should be incorporated into the calibration of error-correction algorithms designed for amplicon sequencing.ResultsIn this paper, we present two new efficient error correction algorithms optimized for viral amplicons: (i) k-mer-based error correction (KEC) and (ii) empirical frequency threshold (ET). Both were compared to a previously published clustering algorithm (SHORAH), in order to evaluate their relative performance on 24 experimental datasets obtained by 454-sequencing of amplicons with known sequences. All three algorithms show similar accuracy in finding true haplotypes. However, KEC and ET were significantly more efficient than SHORAH in removing false haplotypes and estimating the frequency of true ones.ConclusionsBoth algorithms, KEC and ET, are highly suitable for rapid recovery of error-free haplotypes obtained by 454-sequencing of amplicons from heterogeneous viruses.The implementations of the algorithms and data sets used for their testing are available at: http://alan.cs.gsu.edu/NGS/?q=content/pyrosequencing-error-correction-algorithm

Efficient error correction algorithms for gene tree reconciliation based on duplication, duplication and loss, and deep coalescence

BackgroundGene tree - species tree reconciliation problems infer the patterns and processes of gene evolution within a species tree. Gene tree parsimony approaches seek the evolutionary scenario that implies the fewest gene duplications, duplications and losses, or deep coalescence (incomplete lineage sorting) events needed to reconcile a gene tree and a species tree. While a gene tree parsimony approach can be informative about genome evolution and phylogenetics, error in gene trees can profoundly bias the results.ResultsWe introduce efficient algorithms that rapidly search local Subtree Prune and Regraft (SPR) or Tree Bisection and Reconnection (TBR) neighborhoods of a given gene tree to identify a topology that implies the fewest duplications, duplication and losses, or deep coalescence events. These algorithms improve on the current solutions by a factor of n for searching SPR neighborhoods and n2 for searching TBR neighborhoods, where n is the number of taxa in the given gene tree. They provide a fast error correction protocol for ameliorating the effects of gene tree error by allowing small rearrangements in the topology to improve the reconciliation cost. We also demonstrate a simple protocol to use the gene rearrangement algorithm to improve gene tree parsimony phylogenetic analyses.ConclusionsThe new gene tree rearrangement algorithms provide a fast method to address gene tree error. They do not make assumptions about the underlying processes of genome evolution, and they are amenable to analyses of large-scale genomic data sets. These algorithms are also easily incorporated into gene tree parsimony phylogenetic analyses, potentially producing more credible estimates of reconciliation cost.

DNA synthesis, assembly and applications in synthetic biology

The past couple of years saw exciting new developments in microchip-based gene synthesis technologies. Such technologies hold the potential for significantly increasing the throughput and decreasing the cost of gene synthesis. Together with more efficient enzymatic error correction and genome assembly methods, these new technologies are pushing the field of synthetic biology to a higher level.

Area efficient concurrent error detection and correction for parallel filters

In modern signal processing circuits, it is common to find several filters operating in parallel. Proposed is an area efficient technique to detect and correct single errors occurring in pairs of parallel filters that have either the same input data or the same impulse response. The technique uses a primary implementation comprised of two independent filters and a redundant implementation that shares input data between both filters so as to detect and correct errors.The area cost of the proposed scheme is shown to be slightly more than double that of the unprotected filter, whereas the conventional triple modular redundancy solution requires an area three times that of the unprotected filter.

Efficient quantum error correction for fully correlated noise

We investigate an efficient quantum error correction of a fully correlated noise. Suppose the noise is characterized by a quantum channel whose error operators take fully correlated forms given by σx⊗n, σy⊗n and σz⊗n, where n>2 is the number of qubits encoding the codeword. It is proved that (i) n qubits codeword encodes (n−1) data qubits when n is odd and (ii) n qubits codeword implements an error-free encoding, which encode (n−2) data qubits when n is even. Quantum circuits implementing these schemes are constructed.

Continuous-variable quantum-key-distribution protocols with a non-Gaussian modulation

In this paper, we consider continuous-variable quantum key distribution (QKD) protocols which use non-Gaussian modulations. These specific modulation schemes are compatible with very efficient error correction procedures, hence allowing the protocols to outperform previous protocols in terms of achievable range. In their simplest implementation, these protocols are secure for any linear quantum channels (hence against Gaussian attacks). We also show how the use of decoy states makes the protocols secure against arbitrary collective attacks, which implies their unconditional security in the asymptotic limit.

Evaluation of channel adaptive access point systemwith Fano decoding

The popularity of wireless networks is increasing due to their mobility, flexibility, and scalability. High error rate over wireless channels leads current transmission control protocol congestion algorithms to be maintained. Finding approaches at lower layers to overcome this is very efficient and powerful. However, Fano decoding is an efficient error correction mechanism, especially in wireless networks, due to its capability of being adaptive to the channel. In this paper, Stop-and-wait with hybrid automatic repeat request using Fano decoding is adopted at the link layer. Consequently, we propose novel analytical and numerical studies for the distribution of packets in the system of wireless access point or base station. Moreover, the capacity of a sufficient access point system is evaluated numerically.

Verification of Quantum Protocols with a Probabilistic Model-Checker

Channel modeling is crucial for studying the behavior of quantum channels in order to build an efficient error correction scheme in addition to security verification of different protocols. While most current analyses of quantum protocols use a traditional mathematical approach, we employ a simpler probabilistic model checking which is more compatible with classical implementations to investigate the dependency of the security on the quantum channel noise. We also compare a couple of eavesdropping strategies from the security point of view.

Efficient measurement error correction with spatially misaligned data

Association studies in environmental statistics often involve exposure and outcome data that are misaligned in space. A common strategy is to employ a spatial model such as universal kriging to predict exposures at locations with outcome data and then estimate a regression parameter of interest using the predicted exposures. This results in measurement error because the predicted exposures do not correspond exactly to the true values. We characterize the measurement error by decomposing it into Berkson-like and classical-like components. One correction approach is the parametric bootstrap, which is effective but computationally intensive since it requires solving a nonlinear optimization problem for the exposure model parameters in each bootstrap sample. We propose a less computationally intensive alternative termed the "parameter bootstrap" that only requires solving one nonlinear optimization problem, and we also compare bootstrap methods to other recently proposed methods. We illustrate our methodology in simulations and with publicly available data from the Environmental Protection Agency.