• Unified Statistical Channel Model for Turbulence-Induced Fading in Underwater Wireless Optical Communication Systems

      Zedini, Emna; Oubei, Hassan M.; Kammoun, Abla; Hamdi, Mounir; Ooi, Boon S.; Alouini, Mohamed-Slim (IEEE, 2019-01-09)
      A unified statistical model is proposed to characterize turbulence-induced fading in underwater wireless optical communication (UWOC) channels in the presence of air bubbles and temperature gradient for fresh and salty waters, based on experimental data. In this model, the channel irradiance fluctuations are characterized by the mixture Exponential-Generalized Gamma (EGG) distribution. We use the expectation maximization (EM) algorithm to obtain the maximum likelihood parameter estimation of the new model. Interestingly, the proposed model is shown to provide a perfect fit with the measured data under all channel conditions for both types of water. The major advantage of the new model is that it has a simple mathematical form making it attractive from a performance analysis point of view. Indeed, we show that the application of the EGG model leads to closed-form and analytically tractable expressions for key UWOC system performance metrics such as the outage probability, the average bit-error rate, and the ergodic capacity. To the best of our knowledge, this is the first-ever comprehensive channel model addressing the statistics of optical beam irradiance fluctuations in underwater wireless optical channels due to both air bubbles and temperature gradient.
    • Low Abundances but High Growth Rates of Coastal Heterotrophic Bacteria in the Red Sea

      Silva, Luis; Calleja, Maria L.; Huete-Stauffer, Tamara Megan; Ivetic, Snjezana; Ansari, Mohd Ikram; Viegas, Miguel; Moran, Xose Anxelu G. (Frontiers Media SA, 2019-01-07)
      Characterized by some of the highest naturally occurring sea surface temperatures, the Red Sea remains unexplored regarding the dynamics of heterotrophic prokaryotes. Over 16 months, we used flow cytometry to characterize the abundance and growth of four physiological groups of heterotrophic bacteria: membrane-intact (Live), high and low nucleic acid content (HNA and LNA) and actively respiring (CTC+) cells in shallow coastal waters. Chlorophyll a, dissolved organic matter (DOC and DON) concentrations, and their fluorescent properties were also measured as proxies of bottom-up control. We performed short-term incubations (6 days) with the whole microbial community (Community treatment), and with the bacterial community only after removing predators by filtration (Filtered treatment). Initial bacterial abundances ranged from 1.46 to 4.80 × 105 cells mL-1. Total specific growth rates in the Filtered treatment ranged from 0.76 to 2.02 d-1. Live and HNA cells displayed similar seasonal patterns, with higher values during late summer and fall (2.13 and 2.33 d-1, respectively) and lower in late spring (1.02 and 1.01 d-1, respectively). LNA cells were outgrown by the other physiological groups (0.33–1.08 d-1) while CTC+ cells (0.28–1.85 d-1) showed weaker seasonality. The Filtered treatment yielded higher bacterial abundances than the Community treatment in all but 2 of the incubations, and carrying capacities peaked in November 2016 (1.04 × 106 cells mL-1), with minimum values (3.61 × 105 cells mL-1) observed in May 2017. The high temperatures experienced from May through October 2016 (33.4 ± 0.4∘C) did not constrain the growth of heterotrophic bacteria. Indeed, bacterial growth efficiencies were positively correlated with environmental temperature, reflecting the presence of more labile compounds (high DON concentrations resulting in lower C:N ratios) in summer. The overall high specific growth rates and the consistently higher carrying capacities in the Filtered treatment suggest that strong top-down control by protistan grazers was the likely cause for the low heterotrophic bacteria abundances.
    • Prediction of Ignition Regimes in DME/Air Mixtures with Temperature and Concentration Fluctuations

      Luong, Minh Bau; Hernandez Perez, Francisco E.; Sow, Aliou; Im, Hong G. (American Institute of Aeronautics and Astronautics, 2019-01-07)
      The objective of the present study is to establish a theoretical prediction of the autoignition behavior of a reactant mixture for a given initial bulk mixture condition. The ignition regime criterion proposed by Im and coworkers based on the Sankaran number (Sa), which is a ratio of the laminar flame speed to the spontaneous ignition front speed, is extended to account for both temperature and equivalence ratio fluctuations. The extended ignition criterion is then applied to predict the autoignition characteristics of dimethyl ether (DME)/air mixtures and validated by two-dimensional direct numerical simulations (DNS). The response of the ignition mode of DME/air mixtures to three initial mean temperatures of 770, 900 K, and 1045 K lying within/outside the NTC regime, two levels of temperature and concentration fluctuations at a pressure of 30 atm and equivalence ratio of 0.5 is systematically investigated. The statistical analysis is performed, and a newly developed criterion –the volumetric fraction of Sa < 1.0, FSa,S, is proposed as a deterministic criterion to quantify the fraction of heat release attributed to strong ignition. It is found that the strong and weak ignition modes are well captured by the predicted Sa number and FSa,S regardless of different initial mean temperatures and the levels of mixture fluctuations and correlations. Sap and FSa,S demonstrated under a wide range of initial conditions as a reliable criterion in determining a priori the ignition modes and the combustion intensity.
    • Fast Poynting-Vector based wave-mode separation and RTM in 2D elastic TI media

      Liu, Qiancheng; Zhang, Jianfeng; Lu, Yongming; Gao, Hongwei; Liu, Shaolin; Zhang, Hao (Elsevier BV, 2019-01-05)
      The wave-modes in isotropic elastic media are easy to get separated by using Helmholtz decomposition. This method, however, fails in TI (transverse isotropic) media due to the anisotropy, and more sophisticated operators are required. Most of these existing operators are implemented and limited in FD (finite-difference) stencil. We propose a Poynting-vector based method, which separates wave-modes pointwisely, independent of the modeling stencils. In TI media, the Poynting-vector indicates the group-velocity direction while the wave-modes get separated in the polarization-vector direction. We write the relationship between these two directions into a small numerical table by exploiting the phase-velocity direction as a bridge prior to wavefield propagation. During the modeling process, it is easy to estimate the group-velocity direction from the Poynting vector, and then we can get the polarization-vector direction to separate wave-modes by checking the numerical table. We test our method on several TI models. We furthermore apply our method to elastic reverse-time migration (RTM) in TI media.
    • Virus-Mediated Genome Editing in Plants Using the CRISPR/Cas9 System

      Mahas, Ahmed; Ali, Zahir; Tashkandi, Manal; Mahfouz, Magdy M. (Springer New York, 2019-01-04)
      Targeted modification of plant genomes is a powerful strategy for investigating and engineering cellular systems, paving the way for the discovery and development of important, novel agricultural traits. Cas9, an RNA-guided DNA endonuclease from the type II adaptive immune CRISPR system of the prokaryote Streptococcus pyogenes, has gained widespread popularity as a genome-editing tool for use in a wide array of cells and organisms, including model and crop plants. Effective genome engineering requires the delivery of the Cas9 protein and guide RNAs into target cells. However, in planta genome modification faces many hurdles, including the difficulty in efficiently delivering genome engineering reagents to the desired tissues. We recently developed a Tobacco rattle virus (TRV)-mediated genome engineering system for Nicotiana benthamiana. Using this platform, genome engineering reagents can be delivered into all plant parts in a simple, efficient manner, facilitating the recovery of progeny plants with the desired genomic modifications, thus bypassing the need for transformation and tissue culture. This platform expands the utility of the CRISPR/Cas9 system for in planta, targeted genome modification. Here, we provide a detailed protocol explaining the methodologies used to develop and implement TRV-mediated genome engineering in N. benthamiana. The protocol described here can be extended to any other plant species susceptible to systemic infection by TRV. However, this approach is not limited to vectors derived from TRV, as other RNA viruses could be used to develop similar delivery platforms.
    • A standard primary energy approach for comparing desalination processes

      Shahzad, Muhammad Wakil; Burhan, Muhammad; Ng, Kim Choom (Springer Nature, 2019-01-04)
      Considering different grades of energy as equivalent in the desalination industry could have negative economic and environmental consequences. Whereas this approach will suffice for the comparison of same energy input processes, omitting the grade of energy when comparing diverse technologies may lead to incorrect conclusions and, resultantly, inefficient installations. Here, a standard primary energy-based thermodynamic framework is presented that addresses the energy efficacy of assorted desalination processes. Example calculations show that a thermal desalination plant integrated with a power plant consumes 2–3% of input standard primary energy. We also propose a standard universal performance ratio methodology to provide a level playing field for the comparison of desalination processes; this suggest that the majority of desalination processes are operating far from the sustainable zone, with only ~10–13% at the ideal or thermodynamic limit. A proposed roadmap shows that attaining an efficacy level of up to 25–30% of the thermodynamic limit is crucial for achieving the 2030 sustainability development goals for seawater desalination, which will require a technological shift in the capability of dissolved salts separation processes.
    • Design of intense nanoscale stray fields and gradients at magnetic nanorod interfaces

      Ivanov, Yurii P.; Leliaert, Jonathan; Crespo, Adrian; Pancaldi, Matteo; Tollan, Christopher; Kosel, Jürgen; Chuvilin, Andrey; Vavassori, Paolo (American Chemical Society (ACS), 2019-01-04)
      We explore electrodeposited ordered arrays of Fe, Ni and Co nanorods embedded in anodic alumina membranes as a source of intense magnetic stray field gradients localized at the nanoscale. We perform a multiscale characterization of the stray fields using a combination of experimental methods (Magneto-optical Kerr effect, Virtual Bright Field Differential Phase Contrast Imaging) and micromagnetic simulations, and establish a clear correlation between the stray fields and the magnetic configurations of the nanorods. For uniformly magnetized Fe and Ni wires the field gradients vary following saturation magnetization of corresponding metal and the diameter of the wires. In the case of Co nanorods, very localized (~10 nm) and intense (> 1T) stray field sources are associated with the cores of magnetic vortexes. Confinement of that strong field at extremely small dimensions leads to exceptionally high field gradients up to 108 T/m. These results demonstrate a clear path to design and fine-tune nanoscale magnetic stray field ordered patterns with a broad applicability in key nanotechnologies, such as nanomedicine, nanobiology, nanoplasmonics and sensors.
    • Role of MPK4 in pathogen-associated molecular pattern-triggered alternative splicing in Arabidopsis

      Jeremie, Bazin; Mariappan, Kiruthiga Gayathri; Blein, Thomas; Volz, Ronny; Crespi, Martin; Hirt, Heribert (Cold Spring Harbor Laboratory, 2019-01-04)
      Alternative splicing (AS) of pre-mRNAs in plants is an important mechanism of gene regulation in environmental stress tolerance but plant signals involved are essentially unknown. Pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) is mediated by mitogen-activated protein kinases and the majority of PTI defense genes are regulated by MPK3, MPK4 and MPK6. These responses have been mainly analyzed at the transcriptional level, however many splicing factors are direct targets of MAPKs. Here, we studied alternative splicing induced by the PAMP flagellin in Arabidopsis. We identified 506 PAMP-induced differentially alternatively spliced (DAS) genes. Although many DAS genes are targets of nonsense-mediated degradation (NMD), only 19% are potential NMD targets. Importantly, of the 506 PAMP-induced DAS genes, only 89 overlap with the set of 1849 PAMP-induced differentially expressed genes (DEG), indicating that transcriptome analysis does not identify most DAS events. Global DAS analysis of mpk3, mpk4, and mpk6 mutants revealed that MPK4 is a key regulator of PAMP-induced differential splicing, regulating AS of a number of splicing factors and immunity-related protein kinases, such as the calcium-dependent protein kinase CPK28, the cysteine-rich receptor like kinases CRK13 and CRK29 or the FLS2 co-receptor SERK4/BKK1.These data suggest that MAP kinase regulation of splicing factors is a key mechanism in PAMP-induced AS regulation of PTI.
    • Polyoxometalate−Cyclodextrin Metal−Organic Frameworks: From Tunable Intrinsic Microporosity to Customized Storage Functionality

      Yang, Peng; zhao, Wenli; Shkurenko, Aleksander; Belmabkhout, Youssef; Eddaoudi, Mohamed; Dong, Xiaochen; Alshareef, Husam N.; Khashab, Niveen M. (American Chemical Society (ACS), 2019-01-04)
      Self-assembly allows structures to organize themselves into regular patterns by using local forces to find the lowest-energy configuration. However, assembling organic and inorganic building blocks in an ordered framework is hampered by the difficulties of interfacing two dissimilar materials. Herein, the ensemble of polyoxometalates (POMs) and cyclodextrins (CDs) as molecular building blocks (MBBs) has yielded two unprecedented POM-CD-MOFs, namely [PW12O40]3− & α-CD MOF (POT-CD) and [P10P15.5O50]19− & γ-CD MOF (POP-CD), with distinct properties not shared by their isolated parent MBBs. Markedly, the POT-CD features a nontraditional enhanced Li storage behavior by virtue of a unique “amorphization & pulverization” process. This opens the door to a new generation of hybrid materials with tuned structures and customized functionalities.
    • High-throughput 3D modelling to dissect the genetic control of leaf elongation in barley (Hordeum vulgare )

      Ward, Ben; Brien, Chris; Oakey, Helena; Pearson, Allison; Negrão, Sónia; Schilling, Rhiannon K.; Taylor, Julian; Jarvis, David Erwin; Timmins, Andy; Roy, Stuart J.; Tester, Mark A.; Berger, Bettina; van den Hengel, Anton (Wiley, 2019-01-03)
      To optimize shoot growth and structure of cereals, we need to understand the genetic components controlling initiation and elongation. While measuring total shoot growth at high-throughput using 2D imaging has progressed, recovering the 3D shoot structure of small grain cereals at a large scale is still challenging. Here, we present a method for measuring defined individual leaves of cereals, such as wheat and barley, using few images. Plant shoot modelling over time was used to measure the initiation and elongation of leaves in a bi-parental barley mapping population under low and high soil salinity. We detected quantitative trait loci (QTL) related to shoot growth per se, using both simple 2D total shoot measurements and our approach of measuring individual leaves. In addition, we detected QTL specific to leaf elongation and not to total shoot size. Of particular importance was the detection of a QTL on Chromosome 3H specific to the early responses of leaf elongation to salt stress, a locus that could not be detected without the computer vision tools developed in this study. This article is protected by copyright. All rights reserved.
    • Revisiting area risk classification of visceral leishmaniasis in Brazil

      Machado, Gustavo; Alvarez, Julio; Bakka, Haakon Christopher; Perez, Andres; Donato, Lucas Edel; de Ferreira Lima Júnior, Francisco Edilson; Alves, Renato Vieira; Del Rio Vilas, Victor Javier (Springer Nature, 2019-01-03)
      BACKGROUND:Visceral leishmaniasis (VL) is a neglected tropical disease of public health relevance in Brazil. To prioritize disease control measures, the Secretaria de Vigilância em Saúde of Brazil's Ministry of Health (SVS/MH) uses retrospective human case counts from VL surveillance data to inform a municipality-based risk classification. In this study, we compared the underlying VL risk, using a spatiotemporal explicit Bayesian hierarchical model (BHM), with the risk classification currently in use by the Brazil's Ministry of Health. We aim to assess how well the current risk classes capture the underlying VL risk as modelled by the BHM. METHODS:Annual counts of human VL cases and the population at risk for all Brazil's 5564 municipalities between 2004 and 2014 were used to fit a relative risk BHM. We then computed the predicted counts and exceedence risk for each municipality and classified them into four categories to allow comparison with the four risk categories by the SVS/MH. RESULTS:Municipalities identified as high-risk by the model partially agreed with the current risk classification by the SVS/MH. Our results suggest that counts of VL cases may suffice as general indicators of the underlying risk, but can underestimate risks, especially in areas with intense transmission. CONCLUSION:According to our BHM the SVS/MH risk classification underestimated the risk in several municipalities with moderate to intense VL transmission. Newly identified high-risk areas should be further evaluated to identify potential risk factors and assess the needs for additional surveillance and mitigation efforts.
    • Linear kernel tests via emperical likelihood for high dimensional data

      Ding, L.; Liu, Z.; Li, Y.; Liao, S.; Liu, Y.; Yang, P.; Yu, G.; Shao, L.; Gao, Xin (2019-01)
    • Approximate kernel selection with strong approximate consistency

      Ding, L.; Liao, S.; Liu, Y.; Yang, P.; Li, Y.; Pan, Y.; Huang, C.; Shao, L.; Gao, Xin (2019-01)
    • Second order online multitask learning

      Yang, P.; Zhao, P.; Zhou, J.; Gao, Xin (2019-01)
    • Low temperature autoignition of 5-membered ring naphthenes: Effects of substitution

      Fridlyand, Aleksandr; Goldsborough, S. Scott; Rachidi, Mariam El; Sarathy, Mani; Mehl, Marco; Pitz, William J. (Elsevier BV, 2018-12-31)
      The development and design of future internal combustion engines requires fundamental understanding and the capability to model the autoignition and pollutant formation behavior of petroleum-based and other fuels. Naphthenes are an important constituent of gasoline, and they can comprise larger portions of unconventionally-derived gasoline. There is a lack of data and validated models for 5-membered ring naphthenes. In this work, the autoignition characteristics of cyclopentane, and two of its substituted analogues, methylcyclopentane, and ethylcyclopentane are investigated using a twin-piston rapid compression machine. Each fuel is studied at engine-representative conditions: 20, 50 bar and 700–980 K, with mixtures containing stoichiometric fuel/oxygen ratios at various extents of dilution with inert gases. Negative temperature coefficient (NTC) behavior is observed for cyclopentane, though first-stage ignition and associated low temperature heat release behavior are only evident at temperatures below that for the transition to NTC. Pressure is found to have a larger impact on the reactivity than oxygen dilution, with both effects amplified in the NTC region. The cyclopentane experiments in this study are challenged by the sensitivity of this molecule to non-uniform, or mild ignition phenomena within the NTC region. The addition of saturated sidechains in methyl- and ethylcyclopentane significantly increases the reactivity of the molecules, especially at low temperature and NTC conditions. At the highest temperatures though, there is little difference between the three naphthenes. Typical two-stage ignition behavior is observed across a wide range of temperatures for these alkyl cyclopentanes with no mild ignition observed within the NTC region. A recently developed model for cyclopentane is extended to include reactions for methylcyclopentane, and this is used to simulate the new experiments. The simulation results indicate that low temperature reactivity of cyclopentane is dominated by HO2 elimination of the RO2 species producing cyclopentene, and this inhibits autoignition since it is a very stable molecule. When a methyl group is substituted on the ring, additional RO2 isomerization pathways are available, and these substantially increase the fuel reactivity. HO2 elimination is also important with methylcyclopentane, and this leads to significant production of cyclic olefins which can further react to produce diolefins. These findings are consistent with observations that have been made in other experimental apparatuses.
    • Carbohydrate composition of mucus from scleractinian corals from the central Red Sea

      Hadaidi, Ghaida Ali Hassan; Gegner, H. M.; Ziegler, Maren; Voolstra, Christian R. (Springer Nature, 2018-12-31)
      Coral mucus is continuously released by most corals and acts as an important protective barrier and as a substrate for host-associated microbial communities due to its complex composition of carbohydrates, lipids, and proteins. On a reef scale, coral mucus functions as a particle trap, thereby retaining nutrients and energy in the ecosystem. Given the distinct environmental conditions in the Red Sea (high temperature, high salinity, high total alkalinity), we sought to investigate the carbohydrate composition of mucus from five corals from the central Red Sea. Our aim was to assess whether mucus from Red Sea corals is different from what is known from other corals and whether those differences could be aligned to putative beneficial functions with regard to the prevailing environment. Using gas chromatography/mass spectrometry, we detected nine sugars as the main prevalent carbohydrates. Although we detected significant differences between species with regard to the relative abundance of given carbohydrates, the identified sugars resembled those found in mucus from corals elsewhere, and we could corroborate high abundance of arabinose in acroporid corals. Taken together, our results suggest the presence of a common set of carbohydrates across a broad range of coral species from geographically diverse environments, highlighting the important role of mucus with regard to coral and reef ecosystem function.
    • Phenotypic, functional and taxonomic features predict host-pathogen interactions: Table S1; Figure S1

      Liu-Wei, Wang; Kafkas, Senay; Hoehndorf, Robert (Cold Spring Harbor Laboratory, 2018-12-31)
      Identification of host-pathogen interactions (HPIs) can reveal mechanistic insights of infectious diseases for potential treatments and drug discoveries. Current computational methods for the prediction of HPIs often rely on our knowledge on the sequences and functions of pathogen proteins, which is limited for many species, especially for species of emerging pathogens. Matching the phenotypes elicited by pathogens with phenotypes associated with host proteins might improve the prediction of HPIs. We developed an ontology-based method that prioritizes potential interaction protein partners for pathogens using machine learning models. Our method exploits the underlying disease mechanisms by associating phenotypic and functional features of pathogens and human proteins, corroborated by multiple ontologies as background knowledge. Additionally, by embedding the phenotypic information of the pathogens within a formally represented taxonomy, we demonstrate that our model can also accurately predict interaction partners for pathogens without known phenotypes, using a combination of their taxonomic relationships with other pathogens and information from ontologies as background knowledge. Our results show that the integration of phenotypic, functional and taxonomic knowledge not only improves the prediction of HPIs, but also enables us to investigate novel pathogens in emerging infectious diseases.
    • Measuring Canopy Structure and Condition Using Multi-Spectral UAS Imagery in a Horticultural Environment

      Tu, Yu-Hsuan; Johansen, Kasper; Phinn, Stuart; Robson, Andrew (MDPI AG, 2018-12-29)
      Tree condition, pruning and orchard management practices within intensive horticultural tree crop systems can be determined via measurements of tree structure. Multi-spectral imagery acquired from an unmanned aerial system (UAS) has been demonstrated as an accurate and efficient platform for measuring various tree structural attributes, but research in complex horticultural environments has been limited. This research established a methodology for accurately estimating tree crown height, extent, plant projective cover (PPC) and condition of avocado tree crops, from a UAS platform. Individual tree crowns were delineated using object-based image analysis. In comparison to field measured canopy heights, an image-derived canopy height model provided a coefficient of determination (R2) of 0.65 and relative root mean squared error of 6%. Tree crown length perpendicular to the hedgerow was accurately mapped. PPC was measured using spectral and textural image information and produced an R2 value of 0.62 against field data. A random forest classifier was applied to assign tree condition into four categories in accordance with industry standards, producing out-of-bag accuracies >96%. Our results demonstrate the potential of UAS-based mapping for the provision of information to support the horticulture industry and facilitate orchard-based assessment and management.
    • Ordered Sequence Detection and Barrier Signal Design for Digital Pulse Interval Modulation in Optical Wireless Communications

      Guo, Shuaishuai; Park, Ki-Hong; Alouini, Mohamed-Slim (IEEE, 2018-12-28)
      This paper proposes an ordered sequence detection (OSD) for digital pulse interval modulation (DPIM) in optical wireless communications. Leveraging the sparsity of DPIM sequences, OSD shows comparable performance to the optimal maximum likelihood sequence detection (MLSD) with much lower complexity. Compared with the widely adopted sampleby- sample optimal threshold detection (OTD), it considerably improves the bit error rate (BER) performance by mitigating error propagation. Moreover, this paper proposes a barrier signalaided digital pulse interval modulation (BDPIM), where the last of every K symbols is allocated with more power as an inserted barrier signal. BDPIM with OSD (BDPIM-OSD) can limit the error propagation between two adjacent barriers. To reduce the storing delay when using OSD to detect extremely large packets, we propose BDPIM with a combination of OTD and OSD (BDPIM-OTD-OSD), within which long sequences are cut into pieces and separately detected. Approximate upper bounds of the average BER performance of DPIM-OTD, DPIM-OSD, BDPIM-OSD and BDPIM-OTD-OSD are analyzed. Simulations are conducted to corroborate our analysis. Optimal parameter settings are also investigated in uncoded and coded systems by simulations. Simulation results show that the proposed OSD and BDPIM bring significant improvement in uncoded and coded systems over various channels.
    • Promoter analysis and prediction in the human genome using sequence-based deep learning models

      Umarov, Ramzan; Kuwahara, Hiroyuki; Li, Yu; Gao, Xin; Solovyev, Victor (Oxford University Press (OUP), 2018-12-27)
      Motivation:Computational identification of promoters is notoriously difficult as human genes often have unique promoter sequences that provide regulation of transcription and interaction with transcription initiation complex. While there are many attempts to develop computational promoter identification methods, we have no reliable tool to analyze long genomic sequences. Results:In this work we further develop our deep learning approach that was relatively successful to discriminate short promoter and non-promoter sequences. Instead of focusing on the classification accuracy, in this work we predict the exact positions of the TSS inside the genomic sequences testing every possible location. We studied human promoters to find effective regions for discrimination and built corresponding deep learning models. These models use adaptively constructed negative set, which iteratively improves the model's discriminative ability. Our method significantly outperforms the previously developed promoter prediction programs by considerably reducing the number of false positive predictions. We have achieved error-per-1000-bp rate of 0.02 and have 0.31 errors per correct prediction, which is significantly better than the results of other human promoter predictors. Availability:The developed method is available as a web server at http://www.cbrc.kaust.edu.sa/PromID/.