Prediction of new drug-target interactions is critically important as it can lead the researchers to find uses for old drugs and disclose their therapeutic profiles or side effects. However, experimental prediction expensive time-consuming. As a result, computational methods predictioning have gained tremendous interest in recent times. Here we present iDTI-ESBoost, model identification using evolutionary structural features. Our proposed method novel data balancing boosting technique...

Abstract Motivation Extracting useful feature set which contains significant discriminatory information is a critical step in effectively presenting sequence data to predict structural, functional, interaction and expression of proteins, DNAs RNAs. Also, being able filter features with avoid sparsity the extracted require employment efficient selection techniques. Here we present PyFeat as practical easy use toolkit implemented Python for extracting various from To build mainly focused on...

DNA-binding proteins play a very important role in the structural composition of DNA. In addition, they regulate and effect various cellular processes like transcription, DNA replication, recombination, repair modification. The experimental methods used to identify are expensive time consuming thus attracted researchers from computational field address problem. this paper, we present iDNAProt-ES, protein prediction method that utilizes both sequence based evolutionary structure features...

Abstract Although advancing the therapeutic alternatives for treating deadly cancers has gained much attention globally, still primary methods such as chemotherapy have significant downsides and low specificity. Most recently, Anticancer peptides (ACPs) emerged a potential alternative to with fewer negative side-effects. However, identification of ACPs through wet-lab experiments is expensive time-consuming. Hence, computational viable alternatives. During past few years, several ACP...

Identity Management System (IDMS) refers to how users or individuals are identified and authorized use organizational systems services. Since traditional identity management authentication rely heavily on a trusted central authority, they cannot mitigate the effects of single points failure. As decentralized distributed public ledger in peer-to- peer (P2P) network, Blockchain (BC) technology has garnered considerable amount attention field IDMS recent years. Through Self-Sovereign (SSI), can...

Digital radiography is one of the most common and cost-effective standards for diagnosis bone fractures. For such diagnoses expert intervention required which time-consuming demands rigorous training. With recent growth computer vision algorithms, there a surge interest in computer-aided diagnosis. The development algorithms large datasets with proper annotations. Existing X-Ray are either small or lack annotation, hinders machine-learning evaluation relative performance classification,...

Class imbalance classification is a challenging research problem in data mining and machine learning, as most of the real-life datasets are often imbalanced nature. Existing learning algorithms maximise accuracy by correctly classifying majority class, but misclassify minority class. However, class instances representing concept with greater interest than applications. Recently, several techniques based on sampling methods (under-sampling over-sampling class), cost-sensitive methods,...

The task of drug-target interaction prediction holds significant importance in pharmacology and therapeutic drug design. In this paper, we present FRnet-DTI, an auto-encoder based feature manipulation a convolutional neural network classifier for target prediction. Two networks are proposed: FRnet-Encode FRnet-Predict. Here, one model is used the other classification. Using first method FRnet-Encode, generate 4096 features each instances datasets use second method, FRnet-Predict, to identify...

Promoter is a short region of DNA which responsible for initiating transcription specific genes. Development computational tools automatic identification promoters in high demand. According to the difference functions, can be different types. Promoters may have both intra and inter class variation similarity terms consensus sequences. Accurate classification various types sigma still remains challenge. We present iPromoter-BnCNN accurate six - sigma24, sigma28, sigma32, sigma38, sigma54,...

Early purchase prediction plays a vital role for an e-commerce website. It enables e-shoppers to enlist consumers product suggestions, offer discount and many other interventions. Several work has already been done using session log analyzing customer behavior whether he performs on the or not. In most cases, it is difficult find out make list of customers them when their ends. this paper, we propose customer's intention model where can detect purpose earlier. First, apply feature selection...

DNA-binding proteins often play important role in various processes within the cell. Over last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In paper, we propose novel protein prediction method called HMMBinder. HMMBinder uses monogram bigram features extracted from HMM profiles sequences. To best our knowledge, is first application profile based for We applied Support Vector Machines (SVM) as technique Our was...

Network intrusion classification i n t he imbalanced big data environment becomes a significant and important issue in information communications technology (ICT) this digital era. Presently, detection systems (IDSs) are commonly using tool to detect prevent internal external network attacks/intrusions. IDSs majorly bifurcated into host-based network-based systems, use pattern-matching techniques intrusions that known as misuse-based system. Machine learning (ML) mining (DM) algorithms...