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Feature selection is a challenging step in the field of data mining, because there are many local optimal solutions in a feature space. Feature selection can be considered an optimization problem, which requires as few feature combinations as possible and high accuracy. The binary symbiotic organism search (BSOS) algorithm is proposed in this paper. It maps the symbiotic organism search algorithm from a continuous space to a discrete space using an adaptive S-shaped transfer function and can be used to search for the optimal feature subset in a feature selection space. The proposed BSOS algorithm is evaluated using 19 datasets from the UCI repository. First, the results of four basic S-shaped transfer functions are compared with those of the adaptive S-shaped transfer function. Additionally, the experimental results are compared with the results obtained by the popular binary grasshopper optimization, binary gray wolf optimization, traditional binary particle swarm optimization, and binary differential evolution algorithms, which are also employed for feature selection in the existing literature. The experimental results show that the BSOS algorithm can find the fewest number of features in most datasets and achieve a high classification accuracy. Moreover, the experiments also show that the BSOS algorithm is still at a disadvantage in handling low-dimensional datasets and attains low sensitivity in hyperdimensional datasets.

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[Formula: see text]-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577-585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD <2.0 Å) and 78% of the cases are better predicted than the two other methods compared. Our method provides an alternative for modeling TM bitopic dimers of unknown structures for further computational studies. TMDIM is freely available on the web at https://cbbio.cis.umac.mo/TMDIM . Website is implemented in PHP, MySQL and Apache, with all major browsers supported.

BackgroundNon-cemented acetabular cup components demonstrated different clinical performance depending on their surface texture or bearing couple. However, clinical osseointegration needs to be proved for each total joint arthroplasty (TJA) design. Aim of this study was to detect the in vivo migration pattern of a non-cemented cup design, using model-based roentgen stereophotogrammetric analysis with elementary geometrical shape models (EGS-RSA) to calculate early cup migration.MethodsInterchangeable applicability of the model-based EGS-RSA method next to gold standard marker-based RSA method was assessed by clinical radiographs. Afterwards, in vivo acetabular cup migration for 39 patients in a maximum follow up of 120 months (10 years) was calculated using model-based EGS-RSA.ResultsFor the axes with the best predictive capability for acetabular cup loosening, mean (±SD) values were calculated for migration and rotation of the cup. The cup migrated 0.16 (±0.22) mm along the cranio-caudal axis after 24 months and 0.36 (±0.72) mm after 120 months, respectively. It rotated − 0.61 (±0.57) deg. about the medio-lateral axis after 24 months and − 0.53 (±0.67) deg. after 120 months, respectively.ConclusionsInterchangeable applicability of model-based EGS-RSA next to gold standard marker-based RSA method could be shown. Model-based EGS-RSA enables an in vivo migration measurement without the necessity of TJA specific surface models. Migration of the investigated acetabular cup component indicates significant migration values along all the three axes. However, migration values after the second postoperative year were within the thresholds reported in literature, indicating no risk for later aseptic component loosening of this TJA design.