PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7645
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Data Paper Citation - WoS: 15Citation - Scopus: 20Database Covering the Prayer Movements Which Were Not Available Previously(Nature Publishing Group, 2023) Mihçin, Şenay; Şahin, Ahmet Mert; Yılmaz, Mehmet; Alpkaya, Alican Tuncay; Tuna, Merve; Akdeniz, Sevinç; Can, Nuray Korkmaz; Tosun, Aliye; Şahin, SerapLower body implants are designed according to the boundary conditions of gait data and tested against. However, due to diversity in cultural backgrounds, religious rituals might cause different ranges of motion and different loading patterns. Especially in the Eastern part of the world, diverse Activities of Daily Living (ADL) consist of salat, yoga rituals, and different style sitting postures. A database covering these diverse activities of the Eastern world is non-existent. This study focuses on data collection protocol and the creation of an online database of previously excluded ADL activities, targeting 200 healthy subjects via Qualisys and IMU motion capture systems, and force plates, from West and Middle East Asian populations with a special focus on the lower body joints. The current version of the database covers 50 volunteers for 13 different activities. The tasks are defined and listed in a table to create a database to search based on age, gender, BMI, type of activity, and motion capture system. The collected data is to be used for designing implants to allow these sorts of activities to be performed.Article Citation - WoS: 25Citation - Scopus: 21Can Mirbase Provide Positive Data for Machine Learning for the Detection of Mirna Hairpins?(Informationsmanagement in der Biotechnologie e.V. (IMBio e.V.), 2013) Demirci, Müşerref Duygu Saçar; Hamzeiy, Hamid; Allmer, JensExperimental detection and validation of miRNAs is a tedious, time-consuming, and expensive process. Computational methods for miRNA gene detection are being developed so that the number of candidates that need experimental validation can be reduced to a manageable amount. Computational methods involve homology-based and ab inito algorithms. Both approaches are dependent on positive and negative training examples. Positive examples are usually derived from miRBase, the main resource for experimentally validated miRNAs. We encountered some problems with miRBase which we would like to report here. Some problems, among others, we encountered are that folds presented in miRBase are not always the fold with the minimum free energy; some entries do not seem to conform to expectations of miRNAs, and some external accession numbers are not valid. In addition, we compared the prediction accuracy for the same negative dataset when the positive data came from miRBase or miRTarBase and found that the latter led to more precise prediction models. We suggest that miRBase should introduce some automated facilities for ensuring data quality to overcome these problems.