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Item Google page rank site structure strategies for marketing web pages(UMT.Lahore, 2019) Muneeb Ahmad FarooqiToday web is the hub of source and knowledge. There are several Search Engines to categorize the web content and show us on base of our search query. These search engines are continuously visiting the pages/sites and gather the information using different techniques called crawling/spidering. On basis of daily content collection all search engines are managing their own indexes for searches. For every business there is a need to make its pages as most top rated/ranked pages by making structurally and content wise batter so that any crawler can easily crawl it and can rank it among the top 10 results. Also make them simple to compare with other pages which will help the search engines to index it properly. According to Google SERP report 2018 73% users are only using its first page for search results, they never visited the next pages. Google first page is containing 10 results. In this thesis only, structural behavior is being discussed in which internal graphical relationships between pages and the loading time of pages in terms of all supportive content (CSS, JavaScript and videos). Structural overview includes the HTML tags structure which works as tree flow starting from tag and then moving towards child nodes. Pages internal graphical structure is the relation between pages, all pages are connection via links to others sometimes with same site pages and sometimes with other domain pages. To find out this relational structure between internal pages is called Pages graphical structure. Page speed identifies the loading time of a page, it helps search engine to categories pages for mobile devices as well. Sometimes there is a thunder option on mobile search with rank it represents that this page is super-fast in loading. Page loading includes the loading of all content except Ajax base content. Paper explains Ajax base content later in literature review. Using these relationships, it can define the hierarchy of a site same as search engine Page Rank (it is an algorithm used by Google Search to rank web pages). According to Google Page, rank is based on page content, page structure and page loading time. As discussion is only Page structure and page loading time so Google already gave some instructions related to Page structure and page loading speed but those instructions are not enough also it need to discover the new dimensions to make business pages among the top-rated results.Item Boosted deep convolutional neural network based antihypertensive peptide predictor(UMT.Lahore, 2019) ANUM RAUFHeart attack and other heart-related diseases are the main cause of fatalities in the world. These diseases and some other severe diseases like kidney failure and disability are mainly caused by hypertension. There are several drugs available for hypertension treatment but they sometimes cause severe side effects as well. Bioactive peptides that are derived from natural sources and have antihypertensive activity in them can function as likely replacements to pharmacological drugs with no or very fewer side effects. Although these peptides are beneficial it is costly, time-consuming, and need lots of experimentation to find these drugs. So, to overcome this problem we have proposed an automated antihypertensive peptides prediction system which is able to predict whether the given peptide is antihypertensive or not. Recently few researches have conducted for this as well and have satisfactory results but there is a need for more improvement. In this research, we have used two peptide’s sequence datasets (benchmarking and independent dataset) and applied two feature extraction (Amino acid composition and Dipeptide composition) techniques on them. Through these techniques, we have converted the peptide’s sequence dataset into image dataset and further applied deep learning algorithm (convolutional neural network) and machine learning algorithm (support vector machine) on them. While comparing our model with existing models, our model showed greater results with the approximate enhancement of 7-8% of accuracy for both datasets.Item Sequence-Based Prediction of Antibiotic-Resistant Proteins (ARPs) by incorporating position relative moments and statistical features into PseAAC via 5 steps rule(UMT.Lahore, 2019) MIAN MAHMOOD SARWARMuch of our knowledge about antibiotic resistance mechanisms comes from bacteria that cause disease in humans. However, most antibiotics are produced by microorganisms in the environment, suggesting that antibiotic resistance genes have arisen outside the clinic. Studies on soil bacteria have shown that resistance in this environment is widespread. Resistance mechanisms in environmental bacteria may become clinically important as the DNA of these bacteria can be exchanged by the transfer of secondary genes between different species. Knowledge of the development of resistance proteins can influence the design of new antibiotics that can prevent resistance. In order to investigate the mechanism of antibiotic resistance, antibiotic-resistant proteins (ARP) must be identified. However, in vitro, in vivo, and in vivo studies can be difficult, tedious, and expensive, and no ARP predictive model has been proposed. Thus, herein, we report the first and the novel predictor for identification of ARPs using Chou’s pseudo amino acid composition (PseAAC), statistical moments and various position-based features. The predictor is validated through 10-fold cross-validation, which gave 99.3% accurate results. Thus, the proposed predictor can help in predicting the ARPs in an efficient and accurate way and can provide baseline data for the discovery of new drugs and biomarkers.Item Blockchain in healthcare(UMT.Lahore, 2019) Muhammad ZarghamHealth care data is an important wellspring of social insurance knowledge. Sharing of social insurance information is one basic advance to make medicinal services framework more brilliant and improve the nature of human services administration. Medicinal services information, being close to home resource of a patient, ought to be possessed and constrained by patient, rather than being dispersed in various human services frameworks, which anticipates information sharing and put persistent protection in risk. In Healthcare data keeping is one of the main issues, there is medical history of patient for perfect treatments. There is no traceability of prescription given by doctor or laboratory tests. Health data breaching is making billion dollars every year. To understand and explore the issues of doctors and patients’ survey was conducted among different hospitals. In this thesis we cover the contributions made in health sector using Blockchain and also propose a model for improvements in healthcare sector. Blockchain to empower patient to claim, control and offer his/her own information effectively and safely without abusing security, which gives another potential method to improve the knowledge of social insurance frameworks while keeping quiet information private. It guarantees patient possess and control their human services information; straightforward binds together it and makes it conceivable to sort out a wide range of individual medicinal services information for all intents and purposes and effectively. Blockchain innovation has demonstrated its extensive flexibility lately as an assortment of market parts looked for methods for consolidating its capacities into their tasks. With models for open medicinal services the board, client arranged restorative research and medication falsifying in the pharmaceutical division, this report plans to delineate potential impacts, objectives and possibilities associated with this problematic innovation. Block chain’s foundations of decentralization, cryptographic security and immutability make it a strong contender in reshaping the healthcare landscape worldwide. In order to improve our healthcare sector issues and security, Blockchain solutions are explored and can be linked for: securing patient and provider identities, managing pharmaceutical and medical device supply chains, clinical research and data monetization, medical fraud detection; public health surveillance, enabling truly public and open geo-tagged data.Item Text sentiment analysis for categorizing customer response(UMT.Lahore, 2019) AMINA AMJADSocial media has completely reformed the concentration of marketing from a trader to buyer perspective. Nowadays, flow of marketing is controlled by customers rather than companies because of excess of information on social media sites. The Web facilitates us with a virtual world where customers can experience products before buying. Customer behavior includes the intentions and the actions they perform in the consumption and usage of a product. Customer intentions, feelings and activities are constantly changing.In a recent era, the drastic increase in the usage of mobile phones and social media has become a way for knowing customer feedbacks on various platforms and regarding number of services or products. Analyzing the social feedbacks of the customer for business aspect brought a new thought towards sentiment classification. In order to inject accuracy in a prediction model require a wide and clear approach towards data analysis and interpreting user intention. Natural language processing is providing large scope of text analysis by developing opinion classification model. In this thesis we propose the sentiment classification model for customer reviews on unlocked mobile phones obtained from Amazon customer reviews datasets by using sentiment analysis that is based on polar opinions. Customer generated feedback is classified for analysis. From the previous experiments we have decided to apply NLP techniques for this purpose. The primary importance of this research is to establish a better relation between relevantly extracting features and its classification when it comes to text based datasets. We have performed comparative analysis in order to get to know user emotions through feature extraction and classification algorithms. Sentiment text classification and evaluation is experimented and evaluated in different perspective. Customer intentions are classified into positive, negative and neutral sentiments. Data for this purpose is consumed from Amazon customer review .Text is labeled as polarity sentiments through classification with the probable accuracy of 70-93% for positive or negative reviews of customers by using this model. Evaluation of the system is carried out extensively by performance measure techniques. Keywords: Sentiment analysis, Amazon customer reviews, polarity sentiments, comparative analysis.Item Energy efficient clustering using enhanced k-mean algorithm within wsn(UMT.Lahore, 2019) Shahzad RasheedTo make the system energy efficient is the most important and huge task in wireless sensor network. Therefore clustering is one of the greatest technique which is used to make the network efficient. Clustering containing different parameters like threshold, Euclidean distance, and initial energy are used with different values which can cause energy efficiency in sensor nodes. There are 10000 nodes placed at x and y axis providing the specific threshold and by changing the position of base station, we came to the point where energy is thus saving. In this study, K-mean is introduced as an energy efficient clustering algorithm which enhances life time of wireless sensor network. K-mean works on the basis of choosing appropriate cluster head and by choosing appropriate clusters it will balance the load of cluster head as well as prolong the network lifetime. Moreover, by applying unique changings in the algorithm we came to know that enhanced K-mean can save much energy as compare to the existing K-mean. We have modified algorithm on the basis of previous packet and energy record. Our network traffic will be transferred and update its energy record and check itself for remaining energy whether it will be ready to forward next packet or it has to generate signal to other devices about selection of new cluster head node. In this way, most of the energy will be conserved as compared to existing k-mean algorithm, where is no energy sensible record after transmission of traffic. Exiting k-mean algorithm check overall remaining energy record after transmission of huge traffic. Hence, proceeding and check energy in this way can be caused sensor node to deplete its energy very fast. Our experiment results are carried out on Matlab simulators to check the behavior of both algorithms. Results reveals that our new algorithms will conserve most of the energy of sensor nodes and sensor nodes network can be prevailed for long period of time.Item Predicting of nuclear receptor proteins and their subfamilies using sequence features with chous general pseaac(UMT.Lahore, 2019) FAHAD SALEEMNuclear Receptor correspond with an enormous family that contain the transcription factors with ligand-inducible which standardize the gene formulation that exists in cell death and growth, several physiological development, like in homeostasis and embryogenesis. And it’s be appropriate to the superfamily of phylogenetically related proteins and perform the subdivision of proteins into subfamilies due to their domain multiplicity. In this paper automated prediction is performed through computational model based techniques that is most helpful in prediction of Nuclear Receptor Proteins. In this a Nuclear Receptor prediction framework is proposed that based on statistical moments and computational intelligence. In this the new dataset of same classes of Nuclear Receptor subfamilies from UniProt KB is combined with the old used dataset. In this paper we use the multilayer neural network with the statistical moments, and perform training with the help of prediction techniques that based on the back-propagation to get the more accurate and comprehensive output.Item Government revenue enhancement through eis integration and intelligent monitoring(UMT.Lahore, 2019) MUHAMMAD SALEEMThis is a proven fact that tax revenue has a vital significance in the progress and growth of any country. Adopting the same ways in Pakistan, the property tax is collected by Excise, Taxation& Narcotics Control Department (ET&NCD), Government of the Punjab, contributing a second top significant share in total revenue collections of the Department. Currently ET&NC Department using MIS & GIS systems for collection of property tax separately, but details about the properties are still entered manually causing some pilferages to Government exchequer and unable to meet the collection according to its potential demand. This research proposes an intelligent integrated GIS and MIS based system that enables the tax managers to monitor and regulate the property tax collection in an enhanced way. The essential scheme of this particular system devises the escalation of Government Revenue. Certainly, specific endeavor are required for the integration of Enterprise Information Systems (EIS) with Geographic Information System (GIS). The GIS can be implemented using Google Street View (GSV), Google Earth and Google 3D Building Modeler and existing Geo Mappings/Parcels. Moreover, the system can be integrated with Real Estate Agents and District Police system for identification and marking of rental properties. The existing MIS is a joint venture and applied on Property Taxable Circles/Areas in Punjab. This will identify the discrepancy/variation in existing MIS for Property Taxation and prompt & record this discrepancy according to its magnitude. Discrepancy or pilferages in Property Taxation can be minimized by this proposed system and play a key role to collect difference of revenue. The data has been extracted using ETL (Extract, Transform and Load) and a web service (API) from existing available database. The data extraction exhaustively cohere with the business logics of GIS based area determination algorithms. This research thesis, basically, focuses on revenue enhancement by integrating existing Property Tax MIS, GIS & allied technologies, District Police System for Temporary Residence Act and Real Estate Agents System. Researchers believes that proposed research methodology will enhance recovery of property tax from 15 to 20 % annually leading to almost Rs. 2600 million.Item Deep learning based architecture to predict survival time of brain tumor patients(UMT.Lahore, 2019) Muhammad Waqas NadeemDeep learning algorithms enable computational models consist of multiple processing layers for the presentation of data with multiple levels of abstraction. In recent years, usage of deep learning is rapidly proliferating in medical image processing, medical image analysis and bioinformatics. Consequently, deep learning dramatically changed and improved the way of recognition, predication, and diagnosis effectively in numerous areas of healthcare such as, pathology, brain tumor, lungs cancer, abdomen, cardiac, retina and so on. Convolution neural network has great impact in the field of image segmentation and classification. The positional relation between the features may be disregard by the traditional CNN with max-pooling function. Capsule network has the dynamic routing between the network layers that efficiently finds the relation of features. The capsule network with inception block proposed that gives the dynamic kernel size to achieve the state-of-art accuracy for the prediction of survival time for the brain tumor patientsItem Performance analysis and evaluation of rsa and elliptic curve cryptography(UMT.Lahore, 2019) MUHAMMAD OMERThis research presents wide performance revision and investigation of two famous public key cryptosystems, Elliptic Curve Cryptography and RSA. Considered RSA as the first age band in public key cryptography which is well-known since its beginning. Now ECC gradually replacing RSA and start grabbing all the attentions. Beside revision and investigation this research also suggests who is superior based on the experimental and statistical fact. This research shows the outcome of the different characteristic of cryptosystems: encryption and decryption time, key generation time/key size recommended by NIST, signature generation/ signature verification, time complexity, computational cost. After analysis of these outcome this research concludes that ECC way better than RSA. ECC is better in majority aspects. An ECC based cryptosystem is idle special for memory constrained devices. ECC consume less resource and require less computational cost than RSA. Keywords: Elliptic Curve Cryptography, RSA, Cryptosystem security, Public-Key Cryptography, Encryption- DecryptionItem Performance analysis and evaluation of rsa and elliptic curve cryptography(UMT.Lahore, 2019) MUHAMMAD OMERThis research presents wide performance revision and investigation of two famous public key cryptosystems, Elliptic Curve Cryptography and RSA. Considered RSA as the first age band in public key cryptography which is well-known since its beginning. Now ECC gradually replacing RSA and start grabbing all the attentions. Beside revision and investigation this research also suggests who is superior based on the experimental and statistical fact. This research shows the outcome of the different characteristic of cryptosystems: encryption and decryption time, key generation time/key size recommended by NIST, signature generation/ signature verification, time complexity, computational cost. After analysis of these outcome this research concludes that ECC way better than RSA. ECC is better in majority aspects. An ECC based cryptosystem is idle special for memory constrained devices. ECC consume less resource and require less computational cost than RSA. Keywords: Elliptic Curve Cryptography, RSA, Cryptosystem security, Public-Key Cryptography, Encryption- DecryptionItem A framework for the evaluation of safe city projects(UMT.Lahore, 2019) Saba Javed ChatthaSafe City concept is comprised of providing a safe and protected environment for the residents of a city by the state authorities. Different models and concepts for this object are being used to make cities safer and crime free, all over the world. However, while studying and critically analyzing these Safe City Projects(SCP),it transpires that some SCP are up to the mark and delivering while some others are malfunctioning. Moreover, there is no proper evaluation mechanism framework to gauge the efficacy of these SCP. Since the unavailability of a standardized and encompassing mechanism, it is difficult to rank the best among the various prevalent SCP. In this research, an evaluation framework for Safe City Projects is designed to evaluate the different features of SCP according to this framework. Moreover, it will help in ranking the best SCP and will be able to improvise their working accordingly.Item Isumok-pseaac: Identify lysine sumoylation sites using Statistical Moments and pseaac(UMT.Lahore, 2019) MUHAMMAD BAQAR BUTTSUMOylation is a post translational modification that involved in the adaption of cells and functional properties of a large number of proteins. Sumoylation has a key importance in sub cellular concentration, transcriptional synchronization, chromatin remodeling, response to stress and regulation of mitosis. Sumo is associated to development defects and a number of diseases in humans such as cancer, Huntington's, Alzheimer's, Parkinson's diseases, Spinocerebellar ataxia 1 and amyotrophic lateral sclerosis. The covalent bonding of Sumoylation is essential inherit part of the operative characteristics of some other proteins. For that reason, the recognition of feasible SUMOylation sites has importance for research to find out the solution of a number of diseases. We proposed a novel and efficient technique to predict the SUMOylation sites in proteins by incorporating the Chou’s Pseudo Amino Acid Composition (PseAAc), which depends on relative positive features. For the evaluation of our predictor namely SUMOk-PseAAC, self-consistency testing as well as 10-fold cross validation are implemented with the help of accuracy metrics. The result of self-consistency testing was 99.98% Acc, 99.96% Sn, 100% Sp and 99.96% MCC, while the result of 10-fold cross validation was 99.92% Acc, 99.96% Sn, 99.88% Sp and 99.84% MCC. Keywords: SUMOylation, Machine learning, PseAAC, Post-translational modification, 5-step rule, Statistical momentsItem Problem of detecting the presence of anterior cruciate ligament (acl) injuries by using resnet a deep convolutional neural network model(UMT.Lahore, 2019) HASSAN SHABIRThe most commonly injured ligament in the human body is anterior cruciate ligament (ACL) and surgery is often performed for the treatment of ACL. Although this type of damage in knee bone is most common in sportspersons but it can happen to anyone. There are many methods that are used by radiologist to detect ACL tear in knee bone from different sources e.g. X ray based Methods which includes X ray, computed tomography (CT), mammography. For Molecular imaging process we use radiopharmaceuticals and other types of sources are magnetic resonance imaging (MRI) and ultrasound imaging and then it is visually inspected by a radiologist. After examination Radiologist will determine the levels of damage i.e. rupture is full, partial or not injured. Traditionally, for fully-automated or semi-automated segmentation, algorithms that perform well on specific problem domains were developed. Nowadays, with the development of good evaluation metrics for segmentation performance, machine learning methods are more often used. In this thesis we focused on the use of deep learning model ResNet which can help in the ACL- injury classification on Knee MRI dataset. Despite of limitation, with the use of deep learning model we achieved AUC score of 0: 0.91, 1: 0.86, 2: 0.967.Lastly we highlighted some future direction that can also be used for medical image processing.Item Osteoporosis prediction with the help of machine learning in trabecular bone structure using mri(UMT.Lahore, 2019) SADIA QADEERTrabecular bone holds an utmost importance due to its significance regarding early bone loss. Diseases like osteoporosis greatly affect the structure of the Trabecular bone which results into different outcomes like high risk of fracture. The purpose of this paper is to examine the characteristics of the Trabecular bone by using Magnetic Resonance Imaging technique. These characteristics prove to be quite helpful in studying different studies related to Trabecular bone such as osteoporosis. The things that were considered before selection of the articles for the systematic review were language, research field and the electronic sources. Only those articles were selected that were written in English language as it is the most prominent language that is used in scientific, engineering, computer science, and biomedical researches. This literature review was conducted on the articles published between 2000 and 2018. A total of 62 research papers out of 1050 papers were extracted which were according to our topic of review after screening abstract and article content for title and abstract screening. The findings from those researches were compiled in the end of result section. This systematic literature review presents a comprehensive report on the scientific researches and studies that have been done in the medical area concerning Trabecular bone architecture and MRI imaging. Keywords: Magnetic resonance imaging (MRI), High resolution MRI (HR-MRI), Trabecular bone (TB), Bone structureItem Evaluation and selection of active queue management methods based on integrated ahp, topsis and fuzzy topsis(UMT.Lahore, 2019) SAIMA ANWARThe Evaluation and selection of Active Queue Management (AQM) methods is complicated and challenging task. Improper AQM method can cause up-mark and network malfunctioning. To achieve satisfactory performance, various evaluation criteria need to be considered. In order to find the limitations of how the criteria are determined, there is a need to find out how their procedures change according to evaluation and benchmarking process of AQM. This thesis focuses on evaluation and benchmarking of Active Queue Management methods using Multi Criteria Decision Making (MCDM) techniques. MCDM uses different techniques to figure out best alternative from multi criteria and multi alternative conditions. Analytic Hierarchy Process (AHP) is multi criteria decision making technique that is used to assign weights to criteria. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used for ranking and selection of different alternatives by using distance measures. Whereas, FUZZY TOPSIS is used for criteria weightage and alternatives rating. MCDM calculation is performed on AQM methods and it is tried to discuss all these techniques. MCDM uses performance, overhead and configuration criteria to evaluate and select best AQM method that helps to determine solutions for future directions. The results show that Random Early Detection (RED) method got higher ranking score records as compared to other AQM methods. Keywords: Active Queue Management; Multi-Criteria Decision Making; AQM evaluation and benchmarking.Item Quality issues in emerging startups of pakistan(UMT.Lahore, 2019) HASHIR REHMANWith huge growth in the IT industry, many emerging names have come into existence in the Software development business lately. Many startups are just in hurry of delivering the end product and to earn really fast that they do not even bother to go for detailed requirement gathering and analysis, before starting a project. These things can directly affect the quality of the end product. Every software development project starts from the requirement gathering and planning phase, and this phase contributes the most in satisfying the end client by delivering required product. If you do not give proper time and inputs to this phase, even if you succeed in all other phases, you would not be able to deliver the required quality product to the end customer. The thesis provides an overview of the situation of today’s software companies working in Pakistan. Focus is how these software companies are practicing requirement elicitation for their project and on what scale they rate the importance of requirement elicitation team and their work. To verify the concept, a survey was conducted among different software companies based in Pakistan. The results indicate that most of them are lacking proper requirement elicitation team. Many of the companies do not spend proper time on requirement elicitation and most of them do not have any qualified requirement elicitation engineers. There are many known reasons behind this and one common reason is lack of budget. Statistical analysis has been done on requirement elicitation perspective of different software companies and results are concluded from their responses.Item A systematic literature review on video analysis(UMT.Lahore, 2019) Maria Khalid RanaContext: The importance of video analysis is increasing with each passing day. Video analysis is a powerful tool that has applications in almost every field of life. From IOT based systems to big data and deep learning, video analysis is part of every field. Human face recognition is now getting famous due to surveillance and security point of view, it required video stream of human from which facial expressions are extracted in the form of feature matrix. This feature matrix is represented by video captured by camera. Face detection and expression detection also have importance in field of health care. There have been different methods proposed in literature about video analysis that include role of video data in artificial intelligence, big data, deep learning, cloud computing, IoT and DIP. With advancement in different video analysis methods still in terms of computation cost there are not efficient enough methods. Objectives: This study consist of comprehensive systematic review of literature available on video analysis with focus on artificial intelligence, IoT, deep learning, big data, cloud computing and DIP. This study is composed of existing methods and algorithms for the analysis and processing of video with applications in every field of life, from healthcare to security and surveillance to cyber security. The objective of this study is to identify methods on video analysis and classify them on the basis of planning qualitative and quantitative analysis and point out existing limitations in existing methods. Results: For the case of this study, we have gathered 39 papers after the comprehensive study of more than 200 papers. All methods are observed on the basis of end product quality. The basic method to identify difference between each method is done using following measurement factors: PSNR, SNR, and NMSE, quality of video captured, data allocation space and power needed for storage. Conclusion: The need of SLR is due to the fact that new improvement in video processing is becoming more and more each day. New methods are proposed with better accuracy and efficiency, so in order to analyze them in comparative study, SLR is conducted. In the end comparison of all the papers are done in comprehensive manner to give the future direction for the research. Keywords: image caption generation; NLP; LSTM; semantics; systematic literature review, CNN, Deep learning, Big DataItem Modernization of police station record management system in pakistan usingblockchain technology(UMT.Lahore, 2019) Bushra BatoolPolice Station is the backbone of police working. Crime Prevention, Detection and maintaining Law and Order are the primary objects of a Police Station. Since most of the interaction between police and citizen takes place at the police station level. Our police station and Thana culture deter a common man to enter a police station.That’s why Front Desk Project (FDP) was initiated by the Government Pakistan to bridge the gap between police and public in 2015. FDP was aimed to bring educated people in police stations to deal with the complaint by using latest technology to make it easier to lodge a complaint and First Information Report (FIR). FDO is responsible to feed FIR and Challan in a system which is not transparent enough to gain complainant trust and there is no precise platform to improve it. Moreover, there is no direct link between police officers who are responsible to update all data regarding cases in PSRMS (Police Station Record Management System).To address these issues, this research purposed a block chain based transparent, auditable and secure PSRMS platform to avoid illegal exploitation of data and gains complainant’s trust. The proposed model is a proposed architecture of PSRMS, which comprehensively covers Challan data and FIR using smart contract, Meta mask. All action performed on the PSRMS platform is recorded in the database. The proposed model employs smart contracts and complete model to exchange information in sub departments of Police. Finally, Results from performance evaluation show the behavior of chain growing on each node and latency to replicate data on chain in real time.Item Dnarepairproteins-pseaac(UMT.Lahore, 2019) RAHEEL RIAZThe focus of this paper is to analyze a vital molecule of the human body which is called DNA. It is not only found in human beings but also part of plants and animals. It has a lot of information about heritage and informs us that whether we are at the risk of any disease. The damage to the DNA can also change the genetic material and its structure and all the information which it contains. There is a pathway named DNA damage response to perceiving whether the DNA is harmed and also initiates the reaction to the harm. That is why it is important for DNA to develop such components which can repair the harmed DNA. Serious problems like cell passing, apoptosis or oncogenesis occurs when DNA lacks the ability within its neuron to protect itself. The lack of ability to repair DNA also causes serious infections. In this paper, we will highlight the importance of the repair proteins and discuss an efficient method to find the DNA repair proteins and get the best possible results from it. The study will use chou’s 5 step rule and some other techniques to get the best predictions by using an artificial neural network of the algorithm. The 10-fold validation method is also used to validate it on different levels and ensure overall accuracy specificity and the sensitivity. This study will play an important role and propose the fundamental part to the other studies which already exist and some predictions about the repairmen of DNA. The proposed method can offer assistance in DNA foreseeing that too in a productive and best possible way. Keywords: Proteins, DNA damage, DNA repair, DNA repair proteins