We propose an Automatic Gene Ontology (AGO) software as a flexible, open-source Matlab software tool that allows the user to easily compare the results of the bicluster and cluster methods. This software provides several methods to differentiate and compare the results of candidate algorithms. The results reveal that bicluster/cluster algorithms could be considered as integrated modules to recover the interesting patterns in the microarray datasets. The further application of AGO could to solve the dimensionality reduction of the gene regulatory networks. Availability: AGO and help file is

The contribution of this paper is twofold. First, we provide new theoretical insights into the relationship between a string and its reverse: If the Burrows-Wheeler transform (BWT) of a string has been computed by sorting its suffixes, then the BWT and the longest common prefix array of the reverse string can be derived from it without suffix sorting. Furthermore, we show that the longest common prefix arrays of a string and its reverse are permutations of each other. Second, we provide a parallel algorithm that, given the BWT of a string, computes the BWT of its reverse much faster than all

Nile tilapia, Oreochromis niloticus, is the principal fish bred in Egypt. A pilot study was designed to analyze the bacterial composition of the Nile tilapia fish guts from two saltwater lakes in Northern Egypt. Fish samples were obtained from two Delta lakes: Manzala (ML) and Borollus (BL). DNA was extracted, and the bacterial communities in the stomach content were classified (down to the species level) using the 16S rRNA-based analysis. From the two metagenomics libraries in this study, 1,426,740 reads of the amplicon sequence corresponding to 508 total taxonomic operational units were

Cloud-based scientific workflow systems can play an important role in the development of cost effective bioinformatics analysis applications. So far, most efforts for supporting cloud computing in such workflow systems have focused on simply porting them to the cloud environment. The next due steps are to optimize these systems to exploit the advantages of the cloud computing model, basically in terms of managing resource elasticity and the associated business model. In this paper, we introduce new advancements in designing scalable and cost-effective workflows in the cloud using the Tavaxy

One of the key challenges in applying deep learning to solve real-life problems is the lack of large annotated datasets. Furthermore, for a deep learning model to perform well on the test set, all samples in the training and test sets should be independent and identically distributed (i.i.d.), which means that test samples should be similar to the samples that were used to train the model. In many cases, however, the underlying training and test set distributions are different. In such cases, it is common to adapt the test samples by transforming them to their equivalent counterparts in the

Up to 50% of amputees abandon their prostheses, partly due to rapid degradation of the control systems, which require frequent recalibration. The goal of this study was to develop a Kalman filter-based approach to decoding motoneuron activity to identify movement kinematics and thereby provide stable, long-term, accurate, real-time decoding. The Kalman filter-based decoder was examined via biologically varied datasets generated from a high-fidelity computational model of the spinal motoneuron pool. The estimated movement kinematics controlled a simulated MuJoCo prosthetic hand. This clear-box

The strain encoding (SENC) technique encodes regional strain of the heart into the acquired MR images and produces two images with two different tunings so that longitudinal strain, on the short-axis view, or circumferential strain on the long-axis view, are measured. Interleaving acquisition is used to shorten the acquisition time of the two tuned images by 50%, but it suffers from errors in the strain calculations due to inter-tunings motion of the heart, which is the motion between two successive acquisitions. In this work, a method is proposed to correct for the inter-tunings motion by

Cardiac magnetic resonance (CMR) imaging is an important technique for cardiac diagnosis. Measuring the scar in myocardium is important to cardiologists to assess the viability of the heart. Delayed enhancement (DE) images are acquired after about 10 minutes following injecting the patient with contrast agent so the infracted region appears brighter than its surroundings. A common method to segment the infarction from DE images is based on intensity Thresholding. This technique performed poorly for detecting small infarcts in noisy images. In this work we aim to identify the best threshold

An efficient fat suppression method is presented for MR tagging with complementary spatial modulation of magnetization (CSPAMM). In this method, the complementary modulation is applied to the water content of the tissues, while in-phase modulation is applied to the fat content. Therefore, during image reconstruction, the subtraction of the acquired images increases the tagging contrast of the water while cancels the tagging lines of the fat. Compared with the existing fat suppression techniques, the proposed method allows imaging with higher temporal resolution and shorter echo-time without

In the current SARS-CoV2 pandemic, identification and differentiation between SARS-COV2 strains are vital to attain efficient therapeutic targeting, drug discovery and vaccination. In this study, we investigate how the viral genetic code mutated locally and what variations is the Egyptian population most susceptible to in comparison with different strains isolated from Asia, Europe and other countries in Africa. Our aim is to evaluate the significance of these variations and whether they constitute a change on the protein level and identify if any of these variations occurred in the conserved