The continuous increase in the number of attacks on computer networks has raised serious concerns regarding importance establishing a methodology that can learn and adapt to new novel attacks, such model should be able act or react threats within timely manner, so measures are undertaken counter any potential breaches network. Training distinguish between normal anomalous network behavior is difficult task due high dimensionality traffic data. One key requirements successful Anomaly Network...

We present a real-world application that uses quantum computer. Specifically, we train RBM using QA for cybersecurity applications. The D-Wave 2000Q has been used to implement QA. RBMs are trained on the ISCX data, which is benchmark dataset cybersecurity. For comparison, also CD. CD commonly method training. Our analysis of data shows imbalanced. two different schemes balance training before feeding it classifier. first scheme based undersampling benign instances. imbalanced divided into...

The amassed growth in the size of data, caused by advancement technologies and use internet things to collect transmit resulted creation large volumes data an increasing variety types that need be processed at very high speeds so we can extract meaningful information from these massive unstructured data. process mining this is challenging since a lot suffers problem dimensionality. quandary dimensionality represents great challenge controlled through feature selection. Feature selection...

Abstract Classification and data reconstruction using a restricted Boltzmann machine (RBM) is presented. RBM an energy-based model which assigns low energy values to the configurations of interest. It generative model, once trained it can be used produce samples from target distribution. The D-Wave 2000Q quantum computer has been exploit its effect for learning. Bars-and-stripes (BAS) cybersecurity (ISCX) datasets were train RBMs. weights biases RBMs map onto D-Wave. as well image performed....

Mapping RNA sequences to a reference genome often results in high percentages of short reads assigned multiple locations within the genome. These mappings are known as "ambiguous mappings" and discarded by sequence mapping tools pipelines. The number ambiguous these data sets can sometimes be significantly large, occupying certain cases much one third mapped sequences. We developing task specific computer programs that utilize statistical methods an alternative solution for problem. This...

The rapid developments in high-throughput sequencing technologies have allowed researchers to analyze the full genomic sequence of organisms faster and cheaper than ever before. An important application such advancements is identify impact single nucleotide polymorphisms (SNPs) on phenotypes genotypes same species by discovering factors that affect occurrence SNPs. focus this study determine whether climate as main climate, precipitation, temperature affecting a certain geographical area...

Recent advancement in the biological sciences field led to an increase development of large software research projects. These projects are complex and interconnected have proven be hard manage. In many cases, these not completed within their deadlines fail provide users with a reliable piece that can managed maintained future. This observation was also confirmed by scientists working other scientific fields. It is well known non-deterministic nature science requires it always evolving...

PiRNAs are a particular type of small non-coding RNA. They distinct from miRNA in size as well other characteristics, such the lack sequence conservation and increased complexity when compared to their counterparts. PiRNA is considered largest class sRNA that expressed especially animal cells. piRNAs derived long single-stranded RNAs, which transcribed genomic clusters, contrast silencing RNAs. It has been speculated one locus could generate more than piRNA. corresponding repetitive elements...

An organism’s transcriptome is the set of all transcripts within a cell at certain time. We often analyze by quantifying gene expression and performing subsequent analyses such as differential or network analysis. Such analysis helps us in understanding interpreting functional elements genome. Many challenges limit accuracy ability to map RNA-Seq correctly into its genome sequence. Some these are exemplified when mapping sequences fall exon junctions, containing polymorphisms, multiple...

We investigate the task of disease clustering with functional annotations genes from Gene Ontology using biological process aspect. As an unsupervised machine learning step, places communities similar diseases together based on their closeness to one another associated genes. The research work and studies for similarity, relationship, or human information are limited. This builds benefits advances in gene association studies; also Ontology. validated experimental results by comparing...

Computational biology scientific software projects are continuously growing and the volume task of analyzing, designing, implementing, testing, maintaining these to ensure high-quality products only getting harder more complicated. Conventional development methodologies not sufficient in ensuring that is error-free or up standard comparable designed industry. For this reason, it important investigate utilized best engineering practices during their find understand problems arise those...

Intelligent American Sign Language System (IASLS) is a mobile application that allows users to operate their phone or tablet’s camera capture (ASL) and convert it into text which could later be saved as note copied message document. Text captured from translated finger spelling full words in ASL can used send cross-platform other IASLS users, take notes the app, help support an in-person conversation between with ranging abilities. Additionally, who do not know use app’s built-in dictation...