المؤلفون: Suci Aulia, Andriyan Bayu Suksmono, Tati Rajab Mengko, Bachti Alisjahbana

المصدر: IEEE Access, Vol 12, Pp 51364-51380 (2024)

مصطلحات موضوعية: Tuberculosis, Ziehl-Neelsen, acid-fast bacilli, MIDTI, IUATLD, YOLOv7, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

Relation: https://ieeexplore.ieee.org/document/10494737/; https://doaj.org/toc/2169-3536

URL الوصول: https://doaj.org/article/3d6c611abd674f19bb9a82e4a285ebee

المؤلفون: Muhammad Khaerul Naim, Tati Rajab Mengko, Rukman Hertadi, Ayu Purwarianti, Meredita Susanty

المصدر: IEEE Access, Vol 11, Pp 121256-121268 (2023)

مصطلحات موضوعية: Capsule network, DNA-binding proteins, deep learning, machine learning, protein sequence embeddings, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

Relation: https://ieeexplore.ieee.org/document/10302268/; https://doaj.org/toc/2169-3536

URL الوصول: https://doaj.org/article/75397987317b4cd794d15e610d1c1fec

المؤلفون: Untari Novia Wisesty, Ayu Purwarianti, Adi Pancoro, Amrita Chattopadhyay, Nam Nhut Phan, Eric Y. Chuang, Tati Rajab Mengko

المصدر: IEEE Access, Vol 10, Pp 9004-9021 (2022)

مصطلحات موضوعية: Bidirectional long short-term memory, bidirectional gated recurrent unit, DNA sequence, lung cancer, mutation detection, one dimensional convolutional neural network, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

Relation: https://ieeexplore.ieee.org/document/9681069/; https://doaj.org/toc/2169-3536

URL الوصول: https://doaj.org/article/865a8681437e437b835ea38cb8413c9e

المؤلفون: Untari Novia Wisesty, Tati Rajab Mengko, Ayu Purwarianti, Adi Pancoro

المصدر: PLoS ONE, Vol 18, Iss 5 (2023)

مصطلحات موضوعية: Medicine, Science

وصف الملف: electronic resource

Relation: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10212167/?tool=EBI; https://doaj.org/toc/1932-6203

URL الوصول: https://doaj.org/article/2a2ecd9c11824ebc90ab9116b1558077

المؤلفون: Untari N. Wisesty, Tati Rajab Mengko

المصدر: Bulletin of Electrical Engineering and Informatics, 10(4), pp. 2170~2180, (2021-08-01)

مصطلحات موضوعية: This paper aims to conduct an analysis of the SARS-CoV-2 genome variation was carried out by comparing the results of genome clustering using several clustering algorithms and distribution of sequence in each cluster. The clustering algorithms used are K-means, Gaussian mixture models, agglomerative hierarchical clustering, mean-shift clustering, and DBSCAN. However, the clustering algorithm has a weakness in grouping data that has very high dimensions such as genome data, so that a dimensional reduction process is needed. In this research, dimensionality reduction was carried out using principal component analysis (PCA) and autoencoder method with three models that produce 2, and 50 features. The main contributions achieved were the dimensional reduction and clustering scheme of SARS-CoV-2 sequence data and the performance analysis of each experiment on each scheme and hyper parameters for each method. Based on the results of experiments conducted, PCA and DBSCAN algorithm achieve the highest silhouette score of 0.8770 with three clusters when using two features. However, dimensionality reduction using autoencoder need more iterations to converge. On the testing process with Indonesian sequence data, more than half of them enter one cluster and the rest are distributed in the other two clusters, Dimensionality reduction, Genome clustering, Principal component analysis, SARS-CoV-2

Time: 10

Relation: https://doi.org/10.11591/eei.v10i4.2803; oai:zenodo.org:5239798

الاتاحة: https://doi.org/10.11591/eei.v10i4.2803

المؤلفون: Tati Rajab Mengko, Astri H, Vanya Vabrina Valindria, Samekta Hadi, Iwan Sovani

المساهمون: The Pennsylvania State University CiteSeerX Archives

المصدر: http://www.mva-org.jp/Proceedings/2009CD/papers/13-17.pdf.

وصف الملف: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.392.3309; http://www.mva-org.jp/Proceedings/2009CD/papers/13-17.pdf

الاتاحة: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.392.3309
http://www.mva-org.jp/Proceedings/2009CD/papers/13-17.pdf