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Accurate Plant MicroRNA Prediction Can Be Achieved Using Sequence Motif Features

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Journal of Intelligent Learning Systems and Applications 2016年第1期8卷 9-22页

作者： Malik Yousef Jens Allmer waleed khalifa Computer Science The College of Sakhnin Sakhnin Israel The Institute of Applied Research The Galilee Society Shefa-’Amr Israel Molecular Biology and Genetics Izmir Institute of Technology Urla Turkey Bionia Incorporated IZTEKGEB A8 Urla Turkey

MicroRNAs (miRNAs) are short (~21 nt) nucleotide sequences that are either co-transcribed during the production of mRNA or are organized in intergenic regions transcribed by RNA polymerase II. In animals, Drosha, and in plants DCL1 recognize pre-miRNAs which set themselves apart by their characteristic stem loop (hairpin) structure. This structure appears important for their recognition during the process of maturation leading to functioning mature miRNAs. A large body of research is available for computational pre-miRNA detection in animals, but less within the plant kingdom. For the prediction of pre-miRNAs, usually machine learning approaches are employed. Therefore, it is necessary to convert the pre-miRNAs into a set of features that can be calculated and many such features have been described. We here select a subset of the previously described features and add sequence motifs as new features. The resulting model which we called MotifmiRNAPred was tested on known pre-miRNAs listed in miRBase and its accuracy was compared to existing approaches in the field. With an accuracy of 99.95% for the generalized plant model, it distinguishes itself from previously published results which reach an average accuracy between 74% and 98%. We believe that our approach is useful for prediction of pre-miRNAs in plants without per species adjustment.

关键词： MicroRNA Prediction Plant Bioinformatics Machine Learning Sequence Motifs

Sequence Motif-Based One-Class Classifiers Can Achieve Comparable Accuracy to Two-Class Learners for Plant microRNA Detection

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Journal of Biomedical Science and Engineering 2015年第10期8卷 684-694页

作者： Malik Yousef Jens Allmer waleed khalifa The Institute of Applied Research The Galilee Society Shefa Amr Israel Computer Science The College of Sakhnin Sakhnin Israel Molecular Biology and Genetics Izmir Institute of Technology Izmir Turkey Bionia Incorporated IZTEKGEB A8 Izmir Turkey

microRNAs (miRNAs) are short nucleotide sequences expressed by a genome that are involved in post transcriptional modulation of gene expression. Since miRNAs need to be co-expressed with their target mRNA to observe an effect and since miRNAs and target interactions can be cooperative, it is currently not possible to develop a comprehensive experimental atlas of miRNAs and their targets. To overcome this limitation, machine learning has been applied to miRNA detection. In general binary learning (two-class) approaches are applied to miRNA discovery. These learners consider both positive (miRNA) and negative (non-miRNA) examples during the training process. One-class classifiers, on the other hand, use only the information for the target class (miRNA). The one-class approach in machine learning is gradually receiving more attention particularly for solving problems where the negative class is not well defined. This is especially true for miRNAs where the positive class can be experimentally confirmed relatively easy, but where it is not currently possible to call any part of a genome a non-miRNA. To do that, it should be co-expressed with all other possible transcripts of the genome, which currently is a futile endeavor. For machine learning, miRNAs need to be transformed into a feature vector and some currently used features like minimum free energy vary widely in the case of plant miRNAs. In this study it was our aim to analyze different methods applying one-class approaches and the effectiveness of motif-based features for prediction of plant miRNA genes. We show that the application of these one-class classifiers is promising and useful for this kind of problem which relies only on sequence- based features such as k-mers and motifs comparing to the results from two-class classification. In some cases the results of one-class are, to our surprise, more accurate than results from two-class classifiers.

关键词： microRNA One-Class Plant Machine Learning

Computational Approaches for Biomarker Discovery

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Journal of Intelligent Learning Systems and Applications 2014年第4期6卷 153-161页

作者： Malik Yousef Naim Najami Loai Abedallah waleed khalifa The Institute of Applied Research The Galilee Society Shefa Amr Israel Computer Science The College of Sakhnin Sakhnin Israel Department of Biology The Academic Arab College of Education Haifa Israel Department of Mathematics University of Haifa Haifa Israel

Computational biology plays a significant role in the discovery of new biomarkers, the analyses of disease states and the validation of potential biomarkers. Biomarkers are used to measure the progress of disease or the physiological effects of therapeutic intervention in the treatment of disease. They are also used as early warning signs for various diseases such as cancer and inflammatory diseases. In this review, we outline recent progresses of computational biology application in research on biomarkers discovery. A brief discussion of some necessary preliminaries on machine learning techniques (e.g., clustering and support vector machines—SVM) which are commonly used in many applications to biomarkers discovery is given and followed by a description of biological background on biomarkers. We further examine the integration of computational biology approaches and biomarkers. Finally, we conclude with a discussion of key challenges for computational biology to biomarkers discovery.

关键词： Computational Biology Biomarker Discovery Machine Learning

Adaptability of bipedicled scalp advancement flap for coverage of huge scalp defects after tumor resection

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Chinese Journal of Plastic and Reconstructive Surgery 2024年第1期6卷 16-21页

作者： waleed Aldabaany Department of Plastic Surgery Faculty of MedicineFayoum UniversityFayoumEgypt

Background:Several reconstructive techniques have been used to reconstruct scalp *** researchers have studied the utilization of bipedicled scalp advancement flaps for scalp defect *** this study,we will assess the adaptability of a bipedicled scalp advancement flap for coverage of huge scalp defects after tumor ***:This study was performed at the Plastic Surgery Department,Fayoum University Hospital,on 20 patients with huge scalp tumors treated by adequate excision and reconstructed using a bipedicled scalp advancement flap from December 2021 to July ***:The study was conducted on 20 patients:16(80%)were men and 4(20%)were women presenting with large scalp *** mean age was 57.4 years(33-68 years).The sites of the tumors were 10(50%)occipital,6(30%)parietal,and 4(20%)*** major complications occurred postoperatively,and the bipedicled flaps survived well in all cases,with no ***:Huge scalp defects after tumor resection can be safely reconstructed with a large versatile bipedicled advancement scalp flap,either transversely or longitudinally oriented,with favorable functional results and accepted aesthetic results,apart from the alopecic area over the grafted donor site,which can be treated by tissue expansion if desired later.

关键词： Bipedicled advancement flap Huge scalp defects Tumor resection

Smart prediction of liquefaction-induced lateral spreading

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第6期16卷 2310-2325页

作者： Muhammad Nouman Amjad Raja Tarek Abdoun waleed El-Sekelly New York University(NYU)Abu Dhabi Abu Dhabi129188United Arab Emirates University of Management and Technology Lahore54372Pakistan Department of Civil and Environmental Eng. Rensselaer Polytechnic Institute(RPI)1108th StreetJEC 4049TroyNY12180USA Department of Structural Engineering Mansoura UniversityMansoura35516Egypt

The prediction of liquefaction-induced lateral spreading/displacement(Dh)is a challenging task for civil/geotechnical *** this study,a new approach is proposed to predict Dh using gene expression programming(GEP).Based on statistical reasoning,individual models were developed for two topographies:free-face and gently sloping *** with a comparison with conventional approaches for predicting the Dh,four additional regression-based soft computing models,*** process regression(GPR),relevance vector machine(RVM),sequential minimal optimization regression(SMOR),and M5-tree,were developed and compared with the GEP *** results indicate that the GEP models predict Dh with less bias,as evidenced by the root mean square error(RMSE)and mean absolute error(MAE)for training(i.e.1.092 and 0.815;and 0.643 and 0.526)and for testing(i.e.0.89 and 0.705;and 0.773 and 0.573)in free-face and gently sloping ground topographies,*** overall performance for the free-face topology was ranked as follows:GEP>RVM>M5-tree>GPR>SMOR,with a total score of 40,32,24,15,and 10,*** the gently sloping condition,the performance was ranked as follows:GEP>RVM>GPR>M5-tree>SMOR with a total score of 40,32,21,19,and 8,***,the results of the sensitivity analysis showed that for both free-face and gently sloping ground,the liquefiable layer thickness(T_(15))was the major parameter with percentage deterioration(%D)value of 99.15 and 90.72,respectively.

关键词： Lateral spreading Intelligent modeling Gene expression programming(GEP) Closed-form solution Feature importance

New solutions for four novel generalized nonlinear fractional fifth-order equations

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Journal of Ocean Engineering and Science 2024年第1期9卷 59-65页

作者： Mehmet Senol Lanre Akinyemi Henrietta Nkansah waleed Adel Nevsehir HacıBekta¸s Veli University Department of MathematicsNevsehirTurkey Department of Mathematics Lafayette CollegeEastonPennsylvaniaUSA Department of Mathematics University of Cape CoastCape CoastGhana Department of Mathematics and Engineering Physics Faculty of EngineeringMansoura UniversityEgypt UniversitéFrançaise dÉgypte Ismailia Desert RoadEl ShoroukCairoEgypt

In this paper,new four fifth-order fractional nonlinear equations are derived and *** frac-tional terms are defined in the conformable sense and these equations are then solved using two effective methods,namely,the sub-equation and the generalized Kudryashov *** methods were tested on the proposed models and succeeded in finding new solutions with different values of parameters.A graphical representation of some results is provided and proves the efficiency and applicability of the proposed methods for providing solutions with known physical *** methods are good candi-dates for solving other similar problems in the future.

关键词： Conformable derivative Generalized Kudryashov method Sub-equation method Riccati equation Solitons

Improving Prediction Efficiency of Machine Learning Models for Cardiovascular Disease in IoST-Based Systems through Hyperparameter Optimization

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Computers, Materials & Continua 2024年第9期80卷 3485-3506页

作者： Tajim Md.Niamat Ullah Akhund waleed M.Al-Nuwaiser Department of Computer Science and Engineering(CSE) Daffodil International UniversityDhaka1216Bangladesh Graduate School of Science and Engineering Saga UniversitySaga8408502Japan Computer Science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11623Saudi Arabia

This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)*** distinct machine learning approaches were implemented and systematically evaluated before and after hyperparameter *** improvements were observed across various models,with SVM and Neural Networks consistently showing enhanced performance metrics such as F1-Score,recall,and *** study underscores the critical role of tailored hyperparameter tuning in optimizing these models,revealing diverse outcomes among *** Trees and Random Forests exhibited stable performance throughout the *** enhancing accuracy,hyperparameter optimization also led to increased execution *** representations and comprehensive results support the findings,confirming the hypothesis that optimizing parameters can effectively enhance predictive capabilities in cardiovascular *** research contributes to advancing the understanding and application of machine learning in healthcare,particularly in improving predictive accuracy for cardiovascular disease management and intervention strategies.

关键词： Internet of sensing things(IoST) machine learning hyperparameter optimization cardiovascular disease prediction execution time analysis performance analysis wilcoxon signed-rank test

Evaluation of the versatility of perforators-enhanced rhomboid flap technique for ischial sores reconstruction

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Chinese Journal of Plastic and Reconstructive Surgery 2024年第2期6卷 65-71页

作者： waleed Aldabaany Ashraf Hussein Elghamry Montaser Hosny Mohamed Yassin Department of Plastic Surgery Faculty of MedicineFayoum UniversityFayoum63514Egypt

Background: Prolonged pressure on the skin known as pressure sores, can cause frequent injuries to the skin and underlying tissues. However, several prevention approaches, including non-surgical and surgical management,are available. In flap surgery for pressure sores, a variety of flap types may be used;each offers certain benefits and some incidences of complications and recurrence. This study evaluated the versatility of the perforatorenhanced rhomboid flap technique for ischial sore ***: This prospective study was conducted in the Plastic Surgery Department of Fayoum University *** perforator-enhanced rhomboid flap technique was employed in 20 patients with ischial pressure sores who failed to respond to conservative treatment. A proper history was obtained and a preoperative arterial duplex was performed to determine the site of the prominent perforators for their preservation at the base of the *** follow-ups and evaluations were ***: The mean age of the study group was 43.7 ± 13.1, ranging from 19 to 65 years. Moreover, 80% of the participants were males while 20% were female. The main etiology of the sores was paraplegia in 45% of *** mean surface area of sores was 24.8 ± 6.3 cm2. In 75% of cases, the color match of the flap was rated as excellent. Similarly, 70% of the patients rated flap thickness as excellent. In 55% of the cases, the scar appearance was deemed excellent. Overall satisfaction was reported as excellent by 40% of the patients, while only 5% reported poor satisfaction. Approximately, 10% of the cases were identified with seroma, and 30% had wound dehiscence of a mean size of 1.33 ± 0.98 cm and required around 6.8 ± 1.9 weeks to ***: The perforator-enhanced rhomboid flap technique is a versatile method for reconstructing ischial pressure sores owing to its technical ease, short operative time, reliable vascularity, aesthetic outcome, matching skin color, and short recove

关键词： Ischial pressure sores Perforators-enhanced rhomboid flaps Reconstruction

Deep Learning Based Efficient Crowd Counting System

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Computers, Materials & Continua 2024年第6期79卷 4001-4020页

作者： waleed Khalid Al-Ghanem Emad Ul Haq Qazi Muhammad Hamza Faheem Syed Shah Amanullah Quadri Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Centre of Excellence in Cybercrime and Digital Forensics Naif Arab University for Security SciencesRiyadh14812Saudi Arabia Center of Excellence for Information Assurance(COEIA) King Saud UniversityRiyadh12372Saudi Arabia

Estimation of crowd count is becoming crucial nowadays,as it can help in security surveillance,crowd monitoring,and management for different *** is challenging to determine the approximate crowd size from an image of the crowd’s *** in this research study,we proposed a multi-headed convolutional neural network architecture-based model for crowd counting,where we divided our proposed model into two main components:(i)the convolutional neural network,which extracts the feature across the whole image that is given to it as an input,and(ii)the multi-headed layers,which make it easier to evaluate density maps to estimate the number of people in the input image and determine their number in the *** employed the available public benchmark crowd-counting datasets UCF CC 50 and ShanghaiTech parts A and B for model training and testing to validate the model’s *** analyze the results,we used two metrics Mean Absolute Error(MAE)and Mean Square Error(MSE),and compared the results of the proposed systems with the state-of-art models of crowd *** results show the superiority of the proposed system.

关键词： Crowd counting EfficientNet multi-head attention convolutional neural network transfer learning