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IEEE International Conference on bioinformatics and Biomedicine (BIBM)

作者： Feihong Wu Fadi Towfic Drena Dobbs Vasant Honavar Bioinformatics and Computational Biology Graduate Program Iowa State University Ames IA USA

We analyzed the structural properties and the local surface environment of surface amino acid residues of proteins using a large, non-redundant dataset of 2383 protein chains in dimeric complexes from PDB. We compared the interface residues and non-interface residues based on six properties: side chain orientation, surface roughness, solid angle, ex value, hydrophobicity and interface cluster size. The results of our analysis show that interface residues have side chains pointing inward; interfaces are rougher, tend to be flat, moderately convex or concave and protrude more relative to non-interface surface residues. Interface residues tend to be surrounded by hydrophobic neighbors and tend to form clusters consisting of three or more interfaces residues. These findings are consistent with previous published studies using much smaller datasets, while allowing for more qualitative conclusions due to our larger dataset. Preliminary results suggest the possibility of using the six the properties to identify putative interface residues.

关键词： Proteins Rough surfaces Surface roughness bioinformatics Amino acids Solids Sequences Biomedical computing Computer interfaces Biomedical measurements

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Exploring Recurrent Neural Network Models for Depression Detection Through Facial Expressions: A Systematic Literature Review 6

Exploring Recurrent Neural Network Models for Depression Det...

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6th International Conference on Computer and Informatics Engineering, IC2IE 2023

作者： Rumahorbo, Brilyan Nathanael Pardamean, Bens Elwirehardja, Gregorius Natanael Bina Nusantara University Binus Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia

ISBN: (纸本)9798350345162

Major Depressive Disorder (MDD) is a prevalent mental disorder, affecting a significant number of individuals, with estimates reaching 300 million cases worldwide. Currently, the diagnosis of this condition relies heavily on subjective assessments based on the experience of medical professionals. Therefore, researchers have turned to deep learning models to explore the detection of depression. The objective of this review is to gather information on detecting depression based on facial expressions in videos using deep learning techniques. Overall, this research found that RNN models achieved 7.22 MAE for AVEC2014. LSTM models produced 4.83 MAE for DAIC-WOZ, while GRU models achieved an accuracy of 89.77% for DAIC-WOZ. Features like Facial Action Units (FAU), eye gaze, and landmarks show great potential and need to be further analyzed to improve results. Analysis can include applying feature engineering techniques. Aggregation methods, such as mean calculation, are recommended as effective approaches for data processing. This Systematic Literature Review found that facial expressions do have relevant patterns related to MDD. © 2023 IEEE.

关键词： deep learning facial expression GRU LSTM major depressive disorder

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Web Information System Design for Fast Protein Post-Translational Modification Site Prediction 7

Web Information System Design for Fast Protein Post-Translat...

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7th International Conference on Information Management and Technology, ICIMTech 2022

作者： Elwirehardja, Gregorius Natanael Dominic, Nicholas Pardamean, Bens BINUS Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Research Center Bina Nusantara University Bioinformatics and Data Science Jakarta11480 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

In the field of bioinformatics, the protein Post-Translational Modification (PTM) site prediction has been widely studied and Web Information Systems (WIS) has been deployed by researchers for this task. Through a literature review and benchmarking process, we identified the requirements which included quick predictions, efficient memory usage, and input validations. However, no detailed designs have been proposed so far, which may have contributed to some requirements not being implemented in some of the websites. Therefore, we propose a detailed WIS conceptual design, which can be used for predicting the sites of multiple PTM types, equipped with a validation algorithm and compared the usage of various string searching algorithms as well as file storage formats. Experiment results showed that the linear search algorithm is the fastest for this task and storing the protein data in npz format when performing multi-PTMs site prediction can assist in reducing memory usage. The proposed design can be implemented into user-friendly web tools that are both efficient in speed and memory usage in future studies. © 2022 IEEE.

关键词： Forecasting

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Aggregating Structural Features for Computational Analysis of Mutations in BRCT Domains of BRCA1 Protein

Aggregating Structural Features for Computational Analysis o...

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2023 International Conference on Informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Hidayat, Alam Ahmad Nirwantono, Rudi Isnan, Mahmud Trinugroho, Joko Pebrianto Pardamean, Bens Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Mathematics Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Bioinformatics and Data Science Research Center Biotechnology Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Binus Graduate Program Bioinformatics and Data Science Research Center Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350307306

Understanding the mechanistic interpretability of mutation effects in a protein can help predict the clinical implications of the genetic variants. Hence, computational variant effect predictions that involve protein structural features of the protein mutations might be suitable in this case. In this work, we focus on BRCT domains of BRCA1 gene that is widely studied in breast cancer studies. We retrieved 88 selected missense variants found in BRCT domains annotated in both ClinVar and gnomAD databases. To computationally characterize the pathogenic property of the mutations we used two types of features extracted from protein structures: a change in free Gibbs energy and a set of features derived from molecular dynamics simulations of each mutant. Using a dimensional reduction and Gaussian mixture model (GMM)-based clustering we demonstrate that the variants are segregated into two regions that may correspond to their pathogenic status. This method can be a potential computational pipeline for providing the preliminary mechanistic interpretation of mutation effects in terms of their thermodynamic and structural features. © 2023 IEEE.

关键词： Proteins

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Chemical-Induced Disease Detection Using Invariance-based Pattern Learning Model 1

Chemical-Induced Disease Detection Using Invariance-based Pa...

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1st International Workshop on Digital Disease Detection using Social Media, DDDSM 2017, co-located with the 8th International Joint Conference on Natural Language Processing, IJCNLP 2017

作者： Warikoo, Neha Chang, Yung-Chun Hsu, Wen-Lian Institute of Biomedical Informatics National Yang-Ming University Taipei112 Taiwan Bioinformatics Program Taiwan International Graduate Program Institute of Information Science Academia Sinica Taipei115 Taiwan Institute of Information Science Academia Sinica Taipei115 Taiwan Graduate Institute of Data Science Taipei Medical University Taipei106 Taiwan

ISBN: (纸本)9781948087070

In this work, we introduce a novel feature engineering approach named "algebraic invariance" to identify discriminative patterns for learning relation pair features for the chemical-disease relation (CDR) task of BioCreative V. Our method exploits the existing structural similarity of the key concepts of relation descriptions from the CDR corpus to generate robust linguistic patterns for SVM tree kernel-based learning. Preprocessing of the training data classifies the entity pairs as either related or unrelated to build instance types for both inter-sentential and intra-sentential scenarios. An invariant function is proposed to process and optimally cluster similar patterns for both positive and negative instances. The learning model for CDR pairs is based on the SVM tree kernel approach, which generates feature trees and vectors and is modeled on suitable invariance based patterns, bringing brevity, precision and context to the identifier features. Results demonstrate that our method outperformed compared approaches, achieved a high recall rate of 85.08%, and averaged an F1-score of 54.34% without the use of any additional knowledge bases. © 2017 AFNLP

关键词： Forestry

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GranatumX:A Community-engaging, Modularized, and Flexible Webtool for Single-cell Data Analysis

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Genomics, Proteomics & bioinformatics 2021年第3期19卷 452-460页

作者： David G.Garmire Xun Zhu Aravind Mantravadi Qianhui Huang Breck Yunits Yu Liu Thomas Wolfgruber Olivier Poirion Tianying Zhao Cédric Arisdakessian Stefan Stanojevic Lana X.Garmire Department of Electrical Engineering&Computer Science University of MichiganAnn ArborMI 48109USA Epidemiology Program University of Hawaii Cancer CenterHonoluluHI 96813USA Department of Biostatistics University of MichiganAnn ArborMI 48109USA Department of Computational Medicine and Bioinformatics University of MichiganAnn ArborMI 48105USA Molecular Biosciences and Bioengineering Graduate Program University of Hawaii at ManoaHonoluluHI 96822USA

We present GranatumX,a next-generation software environment for single-cell RNA sequencing(scRNA-seq)data *** is inspired by the interactive webtool *** enables biologists to access the latest scRNA-seq bioinformatics methods in a web-based graphical *** also offers software developers the opportunity to rapidly promote their own tools with others in customizable *** architecture of GranatumX allows for easy inclusion of plugin modules,named Gboxes,which wrap around bioinformatics tools written in various programming languages and on various *** can be run on the cloud or private servers and generate reproducible *** is a community-engaging,flexible,and evolving software ecosystem for scRNA-seq analysis,connecting developers with bench *** is freely accessible at http://***/granatumx/app.

关键词： Single-cell RNA sequencing Analysis Pipeline Webtool Module

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The keyword-based and semantic-driven data matching approach for assisting structuralizing the textual clinical documents

The keyword-based and semantic-driven data matching approach...

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International Conference on Biomedical Engineering and Informatics

作者： Chen, Chi-Huang Ping, Xiao-Ou Wang, Zi-Jun Hsieh, Sheau-Ling Chen, Li-Chin Tseng, Yi-Ju Hsu, Ching-Wei Lai, Feipei Department of Electrical Engineering National Taiwan University Taipei Taiwan Graduate Institute of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Electronic and Bioinformatics National Taiwan University Taipei Taiwan EECS International Graduate Program Institute/IT Center National Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)9781424464968

The clinical data stored in the health information system can be categorized as two types including structuralized data and non-structuralized ones. In the paper, a data extraction system is developed to assist data retrieval from the non-structuralized textual clinical documents such as radiology reports, pathology reports, etc. The system provides keyword-based and semantic-driven data matching methodology to extract the specific information from the textual clinical documents. The matching methodology provides the capabilities to recognize the selected keywords and the related semantics in the documents. Through the extraction verification interface, clinicians can extract and verify the matched information semi-automatically. The extracted data can be filled into predefined case-oriented templates. The structuralized data can be stored back into the clinical data warehouse for further analyzing. Moreover, the case-oriented templates can support collecting corresponding extracted data for various researches. ©2010 IEEE.

关键词： Semantics

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Evolution Of SARS-CoV-2 In The Presence Of Vaccines.

Evolution Of SARS-CoV-2 In The Presence Of Vaccines.

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2022 IEEE International Conference on bioinformatics and Biomedicine, BIBM 2022

作者： Marathe, Vishwajeet Yan, Changhui North Dakota State University Department of Computer Scienceline FargoND United States North Dakota State University Department of Computer Science Genomics Phenomics and Bioinformatics Graduate Program FargoND United States

ISBN: (纸本)9781665468190

The COVID pandemic has caused tremendous loss worldwide. Now vaccines are the primary weapon to combat the pandemic. Understanding how SARS-CoV-2, the virus that causes the COVID, may mutate in the presence of the vaccines is critical for designing drugs and vaccines for future variants of the virus. In this study, we investigated the numbers of mutations that SARS-CoV-2 accumulated on each protein over time. We found that different proteins of the virus accumulated different levels of mutations and their mutation rates changed over time following different patterns. We also presented evidence that the mutation of the Spike protein might have been suppressed by the vaccines. This is the first time that such a relation was reported based on real world data. Although the discovery was not meant to be conclusive, this study sheds light onto how the virus may response to the vaccines. If confirmed by further studies, the discovery will have significant impacts on many fields, including drug and vaccine designs. © 2022 IEEE.

关键词： Coronavirus

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iSNP: An integrated, automatically updated SNP database

iSNP: An integrated, automatically updated SNP database

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International Symposium on Health Informatics and bioinformatics (HIBIT)

作者： Levent Çarkacwğlu Ceyhun Gedikoğlu Yeşim Aydin Son Bioinformatics Graduate Program Middle East Technical University 06800 Ankara Turkey Bioinformatics Graduate Program Middle East Technical University Ankara Turkey Health Informatics Department Middle East Technical University Ankara Turkey

Single Nucleotide Polymorphisms (SNP) is a DNA sequence variation that occurs when a single nucleotide differs between members of a biological species or paired chromosomes in an individual. Studies on SNP data are important for scientists to shed light on identifying genetic variations underlying complex diseases. While recent advances in high-throughput genotyping technologies are resulting in data accumulation at large scales, the need for collection and service of this data under a standard format and globally normalized and structured metadata that houses the structured SNP data is becoming essential. Here, we present iSNP that is a regularly updated, machine curated database that holds SNP and its associated metadata from publicly available databases under a structured standard format that can be efficiently utilized within different applications.

关键词： Databases bioinformatics Genomics Humans Diseases

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Rejection of aliases for a direct sampling mixer with complex poles

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2016年第1期136卷 60-67页

作者： Imai, Hiroyuki Wada, Kazuyuki Electrical Engineering Program Graduate School of Science and Technology Meiji University 1-1-1 Higashi-Mita Tama-ku Kawasaki214-8571 Japan Department of Electronics and Bioinformatics School of Science and Technology Meiji University 1-1-1 Higashi-Mita Tama-ku Kawasaki214-8571 Japan

This paper proposes the design scheme of direct sampling mixer (DSM) by which unallowable amplitude characteristics due to aliases spreading over relatively broad band is suppressed. It is pointed out that the periodic frequency characteristic of a stage processing decimated signal causes decrease of attenuation in the stopband of the DSM, and an IIR section with a low decimation rate is employed as the first stage. A DSM the amplitude characteristic of which falls into the spectrum mask for IEEE 802.11 is designed as an example. Simulation results show that the designed DSM satisfies specification widely in not only the passband but also the stopband. It is confirmed that gradual decimation approach or use of a non-decimated section for the first stage is effective. © 2016 The Institute of Electrical Engineers of Japan.

关键词： Bandpass filters

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