Abstract Ran is an evolutionarily conserved eukaryotic GTPase. We previously identified a cDNA of TaRAN1, novel GTPase homologous gene in wheat (Triticum aestivum) and demonstrated that TaRAN1 associated with regulation genome integrity cell division yeast (Saccharomyces cerevisiae) systems. However, much less known about the function RAN plant development. To analyze possible biological roles GTPase, we overexpressed transgenic Arabidopsis (Arabidopsis thaliana) rice (Oryza sativa)....

Alpha-synuclein (SNCA) downregulation shows therapeutic potential for synucleinopathies, including Parkinson's disease (PD). Previously we showed that human (h)SNCA gene silencing using a short hairpin (sh)RNA in rat substantia nigra (SN) protects against hSNCA-induced forelimb deficit, but not dopamine (DA) neuron loss. Furthermore, the shRNA increases cell death vitro, same target sequence embedded microRNA30 transcript (mir30-hSNCA) does not.Examine hSNCA mir30-hSNCA vivo.Rats were...

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by gradual decline in cognitive function. Currently, there are no effective treatments for this condition. Medicine food homology plants have gained increasing attention as potential natural AD because of their nutritional value and therapeutic benefits. In work, we aimed to provide deeper understanding how medicine may help alleviate or potentially treat identifying key targets, pathways, small molecule...

A method that allows a fast and accurate registration of digital tissue models obtained during preoperative, diagnostic imaging with those captured intraoperatively using lower-fidelity ultrasound techniques is presented. Minimally invasive surgeries are often planned high-fidelity medical such as MRI CT imaging. While these allow clinicians to obtain detailed 3D the surgical region interest (ROI), various factors physical changes tissue, in body’s configuration, or apparatus used surgery...

Abstract Small interfering RNAs (siRNAs) may induce to targeted gene knockdown, and the silencing effectiveness relies on efficacy of siRNA. Therefore, task this paper is construct an effective siRNA prediction method. In our work, we try describe from both quantitative qualitative aspects. For analyses, form four groups features, including nucleotide frequencies, thermodynamic stability profile, siRNA-mRNA interaction, mRNA related as a new mixed representation, in which interaction...

Small interfering RNA (siRNA) can be used to post-transcriptional gene regulation by knocking down targeted genes. In functional genomics, biomedical research and cancer therapeutics, siRNA design is a critical topic. Various computational algorithms have been developed select the most effective siRNA, whereas efficacy prediction accuracy not so satisfactory. Many existing methods are based on feature engineering, which may lead biased incomplete features. Deep learning utilizes non-linear...

Abstract There is substantial evidence that age-related ovarian failure in rats preceded by abnormal responsiveness of the neuroendocrine axis to estrogen positive feedback. Because IGF-I seems act as a permissive factor for proper GnRH neuronal response feedback and considering hypothalamic content declines middle-aged (M-A) rats, we assessed effectiveness long-term gene therapy mediobasal hypothalamus (MBH) M-A female extend regular cyclicity preserve structure. We used 3 groups rats: 1...

A multimodal biometric system has been considered a promising technique to overcome the defects of unimodal systems. We have introduced fusion scheme gain better understanding and method for face-iris-fingerprint system. In our case, we use particle swarm optimization train set adaptive Gabor filters in order achieve proper basic functions each modality. For closer analysis texture information, two different local features modality are produced by corresponding coefficients. Next, all...

Protein-protein docking reveals the process and product in protein interactions. Typically, a works with model sampling, then an evaluation method is used to rank near-native models out from large pool of generated decoys. In practice, stage bottleneck perform accurate docking. this paper, PointNet, deep learning algorithm based on point cloud, applied evaluate models. The proposed architecture able directly learn representations carrying geometrical properties atomic attributes 3D...

Abstract Gabor descriptors have been widely used in iris texture representations. However, fixed basic functions cannot match the changing nature of diverse datasets. Furthermore, a single form feature overcome difficulties recognition, such as illumination variations, environmental conditions, and device variations. This paper provides multiple local representations their fusion scheme based on support vector regression (SVR) model for recognition using optimized filters. In our system,...

Protein docking provides a structural basis for the design of drugs and vaccines. Among processes protein docking, quality assessment (QA) is utilized to pick near-native models from numerous candidate conformations, it directly determines final results. Although extensive efforts have been made improve QA accuracy, still bottleneck current systems. In this paper, we presented Deep Graph Attention Neural Network (DGANN) evaluate rank models. DGANN learns inter-residue physio-chemical...

Currently a spam filtering method is extracting attributes from e-mail header and using machine learning methods to classify the sample sets. But as time goes on, spammers transform different ways send spam, which result in great change of spam's header. So defined past could not deal with this sufficiently. This paper extracted all possible forged fields expand feature sets, then used rough set theory Experiment validated more including sets may lead greater performance, terms higher recall...

Abstract Background Several computational tools for predicting protein Ubiquitylation and SUMOylation sites have been proposed to study their regulatory roles in gene location, expression, genome replication. However, existing methods generally rely on feature engineering, ignore the natural similarity between two types of translational modification. This is first all-in-one deep network predict from sequences as well crosstalk simultaneously. Our learning architecture integrates several...

Small interfering RNAs (siRNAs) induce posttranscriptional gene silencing in various organisms. siRNAs targeted to different positions of the same show effectiveness; hence, predicting siRNA activity is a crucial step. In this paper, we developed and evaluated powerful tool named "siRNApred" with new mixed feature set predict activity. To improve prediction accuracy, proposed 2-3NTs as our features. A Random Forest model was constructed using selected by Binary Search Feature Selection...