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Design of a testing strategy using non-animal based test methods: Lessons learnt from the ACuteTox project

TOXICOLOGY IN VITRO 2013年第4期27卷 1395-1401页

作者： Kopp-Schneider, Annette Prieto, Pilar Kinsner-Ovaskainen, Agnieszka Stanzel, Sven German Canc Res Ctr Dept Biostat D-69009 Heidelberg Germany European Commiss Joint Res Ctr Inst Hlth & Consumer Protect I-21027 Ispra VA Italy

In the framework of toxicology, a testing strategy can be viewed as a series of steps which are taken to come to a final prediction about a characteristic of a compound under study. The testing strategy is performed as a single-step procedure, usually called a test battery, using simultaneously all information collected on different endpoints, or as tiered approach in which a decision tree is followed. Design of a testing strategy involves statistical considerations, such as the development of a statistical prediction model. During the EU FP6 ACuteTox project, several prediction models were proposed on the basis of statistical classification algorithms which we illustrate here. The final choice of testing strategies was not based on statistical considerations alone. However, without thorough statistical evaluations a testing strategy cannot be identified. We present here a number of observations made from the statistical viewpoint which relate to the development of testing strategies. The points we make were derived from problems we had to deal with during the evaluation of this large research project. A central issue during the development of a prediction model is the danger of overfitting. Procedures are presented to deal with this challenge. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： classification algorithm Overfitting Prediction model Prediction error Testing strategy

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Protein secondary structure prediction: A survey of the state of the art

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JOURNAL OF MOLECULAR GRAPHICS & MODELLING 2017年 76卷 379-402页

作者： Jiang, Qian Jin, Xin Lee, Shin-Jye Yao, Shaowen Yunnan Univ Sch Informat Kunming Yunnan Peoples R China Yunnan Univ Sch Software Kunming Yunnan Peoples R China Univ Cambridge Queens Coll Cambridge CB3 9ET England

Protein secondary structure prediction (PSSP) is a fundamental task in protein science and computational biology, and it can be used to understand protein 3-dimensional (3-D) structures, further, to learn their biological functions. In the past decade, a large number of methods have been proposed for PSSP. In order to learn the latest progress of PSSP, this paper provides a survey on the development of this field. It first introduces the background and related knowledge of PSSP, including basic concepts, data sets, input data features and prediction accuracy assessment. Then, it reviews the recent algorithmic developments of PSSP, which mainly focus on the latest decade. Finally, it summarizes the corresponding tendencies and challenges in this field. This survey concludes that although various PSSP methods have been proposed, there still exist several further improvements or potential research directions. We hope that the presented guidelines will help nonspecialists and specialists to learn the critical progress in PSSP in recent years. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Protein secondary structure prediction Machine learning Neural networks classification algorithm Feature extraction

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HEALTH MANAGEMENT MONITORING SYSTEM FOR USE IN CLASSIFYING LOWER EXTREMITY MOVEMENTS OF THE ELDERLY

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JOURNAL OF MECHANICS IN MEDICINE AND BIOLOGY 2019年第7期19卷

作者： Kim, Je-Nam Chong, Woo Suk Kim, Seong-Hyun Kim, Kyong Technol Inst Commercializat CAMTIC Adv Mechatron R&D Div Jeonju 54852 South Korea Chungbuk Prov Univ Dept Med & Elect Device Okcheon Gun 29046 South Korea

Knee joints play an indispensable role in the activities of daily living. In particular, the knee joints of the elderly and the physically challenged require continuous care in order to ensure a healthy daily life. This study proposes a health monitoring system for knee joints, which is able to classify lower extremity movements using the angle and acceleration components of these joints. The proposed monitoring system consists of a wearable frame placed on the knee joint, consisting of a sensor part for monitoring the knee joint angle and acceleration and a wireless communication part for transferring bio signals to a smart device. Knee joint angles and accelerations are measured using potentiometers installed at the hinges of the upper and lower parts of the wearable frame and an inertial sensor (IMU) attached to the thigh. Data thus measured are transferred via Bluetooth to an application on a smart device. The proposed system incorporates a classification algorithm for lower extremity movements, which can distinguish users' actions such as sitting, lying, and standing by using real-time measurements of knee joint angles and accelerations. This study shows that the proposed monitoring system detects postures that negatively affect knee joints and informs a user when these postures are adopted, thereby helping to maintain healthy knee joints.

关键词： Health monitoring knee joint angle classification algorithm

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Semi-overlap functions and novel fuzzy reasoning algorithms with applications

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INFORMATION SCIENCES 2022年 614卷 104-122页

作者： Zhang, Xiaohong Wang, Mei Bedregal, Benjamin Li, Mengyuan Liang, Rong Shaanxi Univ Sci & Technol Sch Math & Data Sci Xian 710021 Shaanxi Peoples R China Shaanxi Univ Sci & Technol Sch Elect & Control Engn Xian 710021 Shaanxi Peoples R China Univ Fed Rio Grande do Norte Dept Informat & Matemat Aplicada Campus Univ S-N BR-59072970 Natal Brazil

In order to get a more general result related on fuzzy implications that induced by aggre-gation functions, we relax the definition of general overlap functions, more precisely, removing its right-continuous, and introduce a new kind of aggregation function, which called semi-overlap function. Subsequently, we explore some of their related algebraic properties and its corresponding residual implications. Moreover, serval scholars have pro-vided kinds of methods for fuzzy modus ponens (FMP, for short) problems, such as Zadeh's compositional rule of inference (CRI, for short), Wang's triple I method (TIM, for short) and quintuple implication principle (QIP, for short). Compared with CRI and TIM, QIP has some advantages in solving FMP problems. Based on the above theory foundation of semi -overlap functions and their residual implications, we further consider the QIP for FMP problems. Finally, we propose a new classification algorithm that based on semi-overlap functions and QIP, which called SO5I-FRC algorithm. Through the comparative tests, the average accuracy of SO5I-FRC algorithm is higher than FARC-HD algorithm. The experi-mental results indicate that semi-overlap functions and QIP have certain advantages and a wide range of applications in classification problems.(c) 2022 Elsevier Inc. All rights reserved.

关键词： Overlap function Semi-overlap function Fuzzy reasoning Quintuple implication principle classification algorithm

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Identification of Human Protein Subcellular Location with Multiple Networks

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CURRENT PROTEOMICS 2022年第4期19卷 344-356页

作者： Wang, Rui Chen, Lei Shanghai Maritime Univ Coll Informat Engn Shanghai 201306 Peoples R China

Background: Protein function is closely related to its location within the cell. Determination of protein subcellular location is helpful in uncovering its functions. However, traditional biological experiments to determine the subcellular location are of high cost and low efficiency, which cannot meet today's needs. In recent years, many computational models have been set up to identify the subcellular location of proteins. Most models use features derived from protein sequences. Recently, features extracted from the protein-protein interaction (PPI) network have become popular in studying various protein-related problems. Objective: A novel model with features derived from multiple PPI networks was proposed to predict protein subcellular location. Methods: Protein features were obtained by a newly designed network embedding algorithm, Mnode2vec, which is a generalized version of the classic Node2vec algorithm. Two classic classification algorithms: support vector machine and random forest, were employed to build the model. Results: Such model provided good performance and was superior to the model with features extracted by Node2vec. Also, this model outperformed some classic models. Furthermore, Mnode2vec was found to produce powerful features when the path length was small. Conclusion: The proposed model can be a powerful tool to determine protein subcellular location, and Mnode2vec can efficiently extract informative features from multiple networks.

关键词： Protein subcellular location multiple networks network embedding algorithm Mnode2vec node2vec classification algorithm

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A computational platform to identify origins of replication sites in eukaryotes

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BRIEFINGS IN BIOINFORMATICS 2021年第2期22卷 1940-1950页

作者： Dao, Fu-Ying Lv, Hao Zulfiqar, Hasan Yang, Hui Su, Wei Gao, Hui Ding, Hui Lin, Hao Univ Elect Sci & Technol China Ctr Informat Biol Chengdu 610054 Peoples R China

The locations of the initiation of genomic DNA replication are defined as origins of replication sites (ORIs), which regulate the onset of DNA replication and play significant roles in the DNA replication process. The study of ORIs is essential for understanding the cell-division cycle and gene expression regulation. Accurate identification of ORIs will provide important clues for DNA replication research and drug development by developing computational methods. In this paper, the first integrated predictor named iORI-Euk was built to identify ORIs in multiple eukaryotes and multiple cell types. In the predictor, seven eukaryotic (Homo sapiens, Mus musculus, Drosophila melanogaster, Arabidopsis thaliana, Pichia pastoris, Schizosaccharomyces pombe and Kluyveromyces lactis) ORI data was collected from public database to construct benchmark datasets. Subsequently, three feature extraction strategies which are k-mer, binary encoding and combination of k-mer and binary were used to formulate DNA sequence samples. We also compared the different classification algorithms' performance. As a result, the best results were obtained by using support vector machine in 5-fold cross-validation test and independent dataset test. Based on the optimal model, an online web server called iORI-Euk (http://***/server/iO RI- Euk/) was established for the novel ORI identification.

关键词： origins of replication site eukaryote feature extraction webserver classification algorithm

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The Anatomy of Sorting-Evidence From Danish Data

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ECONOMETRICA 2023年第6期91卷 2409-2455页

作者： Lentz, Rasmus Piyapromdee, Suphanit Robin, Jean-Marc Univ Wisconsin Dept Econ Madison WI 53715 USA Univ Aarhus Dale T Mortensen Ctr Aarhus Denmark UCL Dept Econ London England Sci Po Sci Paris France

In this paper, we formulate and estimate a flexible model of job mobility and wages with two-sided heterogeneity. The analysis extends the finite mixture approach of Bonhomme, Lamadon, and Manresa (2019) and Abowd, McKinney, and Schmutte (2019) to develop a new classification Expectation-Maximization algorithm that ensures both worker and firm latent-type identification using wage and mobility variations in the data. Workers receive job offers in worker-type segmented labor markets. Offers are accepted according to a logit form that compares the value of the current job with that of the new job. In combination with flexibly estimated layoff and job finding rates, the analysis quantifies the four different sources of sorting: job preferences, segmentation, layoffs, and job finding. Job preferences are identified through job-to-job moves in a revealed preference argument. They are in the model structurally independent of the identified job wages, possibly as a reflection of the presence of amenities. We find evidence of a strong pecuniary motive in job preferences. While the correlation between preferences and current job wages is positive, the net present value of the future earnings stream given the current job correlates much more strongly with preferences for it. This is more so for short- than long-tenure workers. In the analysis, we distinguish between type sorting and wage sorting. Type sorting is quantified by means of the mutual information index. Wage sorting is captured through correlation between identified wage types. While layoffs are less important than the other channels, we find all channels to contribute substantially to sorting. As workers age, job arrival processes are the key determinant of wage sorting, whereas the role of job preferences dictate type sorting. Over the life cycle, job preferences intensify, type sorting increases, and pecuniary considerations wane.

关键词： Heterogeneity wage distributions employment and job mobility mutual information finite mixtures EM algorithm classification algorithm sorting decomposition of wage inequality

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Effective DNA binding protein prediction by using key features via Chou's general PseAAC

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JOURNAL OF THEORETICAL BIOLOGY 2019年 460卷 64-78页

作者： Adilina, Sheikh Farid, Dewan Md Shatabda, Swakkhar United Int Univ Dept Comp Sci & Engn Plot 2Madani Ave Dhaka 1212 Bangladesh

DNA-binding proteins (DBPs) are responsible for several cellular functions, starting from our immunity system to the transport of oxygen. In the recent studies, scientists have used supervised machine learning based methods that use information from the protein sequence only to classify the DBPs. Most of the methods work effectively on the train sets but performance of most of them degrades in the independent test set. It shows a room for improving the prediction method by reducing over-fitting. In this paper, we have extracted several features solely using the protein sequence and carried out two different types of feature selection on them. Our results have proven comparable on training set and significantly improved on the independent test set. On the independent test set our accuracy was 82.26% which is 1.62% improved compared to the previous best state-of-the-art methods. Performance in terms of sensitivity and area under receiver operating characteristic curve for the independent test set was also higher and they were 0.95 and 0.823 respectively. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： DNA binding proteins classification algorithm Sequence based features Feature selection Handling overfitting Independent test set

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Enhancing the Reliability of Wi-Fi Network Using Evil Twin AP Detection Method Based on Machine Learning

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JOURNAL OF INFORMATION PROCESSING SYSTEMS 2020年第3期16卷 541-556页

作者： Seo, Jeonghoon Cho, Chaeho Won, Yoojae Chungnam Natl Univ Dept Comp Sci Engn Daejeon South Korea

Wireless networks have become integral to society as they provide mobility and scalability advantages. However, their disadvantage is that they cannot control the media, which makes them vulnerable to various types of attacks. One example of such attacks is the evil twin access point (AP) attack, in which an authorized AP is impersonated by mimicking its service set identifier (SSID) and media access control (MAC) address. Evil twin APs are a major source of deception in wireless networks, facilitating message forgery and eavesdropping. Hence, it is necessary to detect them rapidly. To this end, numerous methods using clock skew have been proposed for evil twin AP detection. However, clock skew is difficult to calculate precisely because wireless networks are vulnerable to noise. This paper proposes an evil twin AP detection method that uses a multiple-feature-based machine learning classification algorithm. The features used in the proposed method are clock skew, channel, received signal strength, and duration. The results of experiments conducted indicate that the proposed method has an evil twin AP detection accuracy of 100% using the random forest algorithm.

关键词： Access Point classification algorithm Clock Skew Evil Twin AP Rogue AP Wireless Network

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Screening gene signatures for clinical response subtypes of lung transplantation

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MOLECULAR GENETICS AND GENOMICS 2022年第5期297卷 1301-1313页

作者： Zhang, Yu-Hang Li, Zhan Dong Zeng, Tao Chen, Lei Huang, Tao Cai, Yu-Dong Shanghai Univ Sch Life Sci Shanghai 200444 Peoples R China Harvard Med Sch Brigham & Womens Hosp Channing Div Network Med Boston MA 02115 USA Jilin Engn Normal Univ Coll Food Engn Changchun 130052 Peoples R China Chinese Acad Sci Univ Chinese Acad Sci Biomed Big Data Ctr Shanghai Inst Nutr & HlthCAS Key Lab Computat Bi Shanghai 200031 Peoples R China Shanghai Maritime Univ Coll Informat Engn Shanghai 201306 Peoples R China Chinese Acad Sci Univ Chinese Acad Sci Shanghai Inst Nutr & Hlth CAS Key Lab Tissue Microenvironm & Tumor Shanghai Peoples R China

Lung is the most important organ in the human respiratory system, whose normal functions are quite essential for human beings. Under certain pathological conditions, the normal lung functions could no longer be maintained in patients, and lung transplantation is generally applied to ease patients' breathing and prolong their lives. However, several risk factors exist during and after lung transplantation, including bleeding, infection, and transplant rejections. In particular, transplant rejections are difficult to predict or prevent, leading to the most dangerous complications and severe status in patients undergoing lung transplantation. Given that most common monitoring and validation methods for lung transplantation rejections may take quite a long time and have low reproducibility, new technologies and methods are required to improve the efficacy and accuracy of rejection monitoring after lung transplantation. Recently, one previous study set up the gene expression profiles of patients who underwent lung transplantation. However, it did not provide a tool to predict lung transplantation responses. Here, a further deep investigation was conducted on such profiling data. A computational framework, incorporating several machine learning algorithms, such as feature selection methods and classification algorithms, was built to establish an effective prediction model distinguishing patient into different clinical subgroups, corresponding to different rejection responses after lung transplantation. Furthermore, the framework also screened essential genes with functional enrichments and create quantitative rules for the distinction of patients with different rejection responses to lung transplantation. The outcome of this contribution could provide guidelines for clinical treatment of each rejection subtype and contribute to the revealing of complicated rejection mechanisms of lung transplantation.

关键词： Lung transplantation Gene signatures classification algorithm Feature selection

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