2022 10th International Conference on Bioinformatics and Computational Biology (ICBCB)最新文献

{"title":"Sequence Assembly Method Based on a Single Reference Genome","authors":"Sheng Jiquan, Zeng Cheng","doi":"10.1109/icbcb55259.2022.9802131","DOIUrl":"https://doi.org/10.1109/icbcb55259.2022.9802131","url":null,"abstract":"Although genetic sequencing technology has made great progress, read errors and large repetitive regions still occur during the genome assembly process. Many current assembly methods typically yield only sets of contigs whose relative positions and orientations along the sequenced genome are unknown. In order to further obtain its correct and complete sequence, this paper proposes a new sequence assembly method based on a single reference genome of similar species: BRS. For a specific species, assuming that its own reference genome is unknown, due to the high genetic similarity between similar species. the reference genome of similar species is used as an aid and the alignment tool is used to compare the contig collection and the reference genome of similar species. We analyze the alignment information and determine the direction and position of the contigs according to the final alignment result and complete the sequence assembly of the gene. The BRS method is compared with two other common methods: RaGOO and Ragout2 on two bacterial datasets. The experimental results show that this method can indeed achieve good results.","PeriodicalId":429633,"journal":{"name":"2022 10th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115683666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ICBCB 2022 Cover Page","authors":"","doi":"10.1109/icbcb55259.2022.9802483","DOIUrl":"https://doi.org/10.1109/icbcb55259.2022.9802483","url":null,"abstract":"","PeriodicalId":429633,"journal":{"name":"2022 10th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116969559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Association between Cognition and Metabolic Biomarkers among Elder Chinese Population: Findings from the Longitudinal Cohort CHARLS Study","authors":"Diefei Chen","doi":"10.1109/icbcb55259.2022.9802462","DOIUrl":"https://doi.org/10.1109/icbcb55259.2022.9802462","url":null,"abstract":"Background: China is one of the countries with the largest burden of cognitive impairment and dementia worldwide, however, studies elucidating potential mechanisms have been relatively scarce in this population. It has been reported that inflammatory or kidney-related metabolic biomarkers are associated with cognitive function and risk for developing dementia among older adults.Objectives: Using the Chinese Health and Retirement Longitudinal Study (CHARLS) database, we aim to investigate the cross-sectional correlations between inflammation or kidney-related metabolic biomarkers and cognitive measure outcomes that were ascertained in the same wave, as well as measures lagged by data collection waves.Methods: After excluding older participants with diagnosed memory problems, we analyzed the association of each blood-based biomarker (e.g. White Blood Cell count, Creatinine, Blood Urea Nitrogen, Uric Acid, Cystatin C, C-Reactive protein) with scores from five cognitive tests (e.g. Immediate Word Recall, Delayed Word Recall, Serial 7’s, Date Naming, Picture Drawing) as well as a total summary recall score. We performed linear regressions for continuous outcomes and logistic regressions for dichotomized outcomes. Covariates such as age, sex, education, smoking, drinking, and residency were also included in multivariate models. We then identified biomarkers that have shown consistent associations across waves.Results: Having elevated CRP (1-3 mg/L) was found to be positively associated with scores from Immediate Word Recall, Delayed Word Recall, Serial 7’s, Date Naming, Picture Drawing. Abnormal levels of Creatinine (Low: <0.74 mg/dl for male and <0.59 mg/dl for female; High:>1.35 mg/dl for male and >1.04 mg/dl for female) were associated with poorer test scores. We did not find consistency in associations between other biomarkers included in this analysis and cognitive test scores.Conclusions: Our study established cross-sectional and longitudinal associations between inflammatory or kidney-related metabolic biomarkers and specific domains of cognition. We also provided biomarker evidence on indicators of kidney function and inflammation for dementia research. Our study results may be used for future intervention exploration by broadening the paradigm in dementia etiology research beyond the amyloid-cascade theory.","PeriodicalId":429633,"journal":{"name":"2022 10th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133081516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Principal Component Analysis Provides Insights on the Evolutionary Divergence of Conotoxins","authors":"Akira Kikuchi, L. Tayo","doi":"10.1109/icbcb55259.2022.9802130","DOIUrl":"https://doi.org/10.1109/icbcb55259.2022.9802130","url":null,"abstract":"Conotoxins are fast-evolving and highly diverse small, structured peptides found in venoms of predatory marine gastropods of the genus Conus. They are diverse yet exhibit superior stability, potency, and selectivity for various target receptors and subtypes; hence, they were proven valuable probes for drug discovery studies and models for protein evolution. The data structure of conotoxin peptide sequences in each gene superfamily was analyzed. Feature extraction showed diet- and geographical region-specific gene superfamilies. Using fast-Fourier transform (FFT) and principal component analysis (PCA), data structures indicated patterns of sequence similarity in conopeptides isolated in the same diet type. Clusters based on diet are prominent in the PCA plots and dendrograms. PCA clustering, node grouping, and feature extraction suggest the increasing role of dietary preference, providing insights on the driving force that pushed conotoxins to diverge and diversify.","PeriodicalId":429633,"journal":{"name":"2022 10th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"722 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133216150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic Epidemiology of Porcine Epidemic Diarrhea Virus in Jiangsu Province of China from 2017 to 2018","authors":"Jie Li, Mengjiao Li, Xiangyin Gu, Y. Huang, Jiating Qian, Han Xu","doi":"10.1109/icbcb55259.2022.9802488","DOIUrl":"https://doi.org/10.1109/icbcb55259.2022.9802488","url":null,"abstract":"With the development of sequencing technology, our capability to fathom virus has been revolutionized and ever more promising. Spike gene is diverse and crucial for understanding the genetic relations of porcine epidemic diarrhea virus field strains. In this study we deployed a classical approach to examine the epidemic trend of PEDV in Jiangsu from 2017 to 2018, one of the eight most critically infected provinces since the late 2010 outbreak in China. Here, S1 regions of spike gene from 63 selected strains were clustered along with 24 references. We found that these sequences were genetically more diverse through time. Among these strains, G1b and G2b clusters accounted for 4.76% and 95.24%, respectively, namely G2b was the most dominant cluster in Jiangsu Province, China. Furthermore, we made a more detailed analysis to demonstrate the corresponding relationship between specific mutation sites and virus subtype.","PeriodicalId":429633,"journal":{"name":"2022 10th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"40 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115630823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Denovo Rebuilding Approach to the Working Principle of Living Things","authors":"Shijian Chen, Xiaojie Liu, Qiang Huang","doi":"10.1109/icbcb55259.2022.9802476","DOIUrl":"https://doi.org/10.1109/icbcb55259.2022.9802476","url":null,"abstract":"The aim of our work is to build a living thing in silicon by denovo assumptions and theories so as to understand life's working principle. The random collision set is the denovo point of our theory. This point paved our way to a system, which is both biochemically realizable and higher level emergent phenomenon reachable. Guided by our rebuilding theorem, we introduce biologically meaningful molecules and establish the full-quasi-autonomous Genome-Metabolic (G-M) system. Then an evolutionary computational method is applied to make higher-level biological functions to emerge. It is successfully evolved into a dynamic autonomous system. We analyze the behaviors and structure of the system and find that well accepted phenomena, such as cycle of negative feedback chains, gene regulatory network emerge as expected. These are verifications of our theory, which means that our approach has the power to shed light on the working principle of living things.","PeriodicalId":429633,"journal":{"name":"2022 10th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131454672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monitoring Worldwide Trends of Expressed Depression on Twitter before and after COVID-19 Vaccine Releases","authors":"He Wang, Long Ma, Yunye Yu","doi":"10.1109/icbcb55259.2022.9802477","DOIUrl":"https://doi.org/10.1109/icbcb55259.2022.9802477","url":null,"abstract":"Since the COVID-19 pandemic broke out in early 2020, the global community has been living in fear, stress, and isolation. The COVID-19 vaccine might provide a solution to the ongoing global crisis. This study seeks to monitor the trends of depression that have been discussed on Twitter before and after the COVID-19 vaccine was released and explores whether such differences were universal or geographical. Specifically, this paper investigates the variations in sentiment in different geographic regions and the change of sentiments before and after the vaccine release. We collect tweets containing keywords \"COVID-19\" and “depression” and rely on releasing date of the COVID-19 vaccine as a division point. The experiment results reveal that topics related to depression varied significantly across different regions before and after the COVID-19 vaccine was released. For example, tweets posted in America are focused on social lockdown and infection with COVID-19 when referring to depression. In contrast, tweets from European countries discuss more typical depression symptoms and Brexit. The tweets posted in Asian, African, and Oceanian contain more discussions on stress. Our analysis further indicates that Asian users’ stress is mainly from the study while Oceanian and African users' stress is primarily from family. Another interesting finding in our paper is that tweets show a common desire for normal social activities after the vaccine release, regardless of geographical locations.","PeriodicalId":429633,"journal":{"name":"2022 10th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132920694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-sample Mendelian Randomization Study for Schizophrenia and Cancers","authors":"K. Yuan, Weichen Song, Zhe Liu, G. Lin, Shun-ying Yu","doi":"10.1109/icbcb55259.2022.9802125","DOIUrl":"https://doi.org/10.1109/icbcb55259.2022.9802125","url":null,"abstract":"The causal relationship between cancer and schizophrenia remains controversial. Some published studies describing the role of schizophrenia as a protective factor for cancer by cohort studies or meta-analysis, while others have observed the opposite. Here in this article, we investigated potential genetic relationships between schizophrenia and 13 cancers through two-sample Mendelian randomization (2SMR) on public GWAS summary statistics to fill in this gap. Combining cancer eQTL data, we identified the cancer-related genes according to schizophrenia SNP locus and then performed relative downstream analysis. We discovered that the genetic susceptibility to schizophrenia lead to an increasing risk of breast cancer (odds ratio [OR] per log-odds increase in schizophrenia risk: 1.041, 95% confidence interval [CI]: 1.014-1.067, p=0.0026), ovarian cancer (OR, 1.086; 95%CI, 1.031-1.143; p=0.0018), and thyroid cancer (OR, 1.559; 95% CI, 1.055-2.303; p=0.0256). Furthermore, using the eQTL data, we identified the common genes through mapping to the schizophrenia SNP locus. AS3MT, SFXN2 and PCCB are differentially expressed in cancers and AS3MT, SFXN2 have a significant effect on prognosis. In addition, we noticed that schizophrenia will affect the level of thyroid-stimulating hormone (OR, 1.095; 95% CI, 1.006-1.191; p = 0.0354), which may further affect the level of estrogen and the risk of the above three cancers. In sum, under the 2SMR assumption, our findings offers some important insights into a risk-increasing effect of schizophrenia on three cancers risk. AS3MT, SFXN2 and PCCB may be potential biomarkers for preventing breast cancer and thyroid cancer in patients with schizophrenia.","PeriodicalId":429633,"journal":{"name":"2022 10th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130555650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combining the Transformers and CNNs for Renal Parenchymal Tumors Diagnosis","authors":"Shuai Wang, Lian-yu Zhang, Hui-qian Du, Yan Chen, Yao Zheng, Wenbo Mei","doi":"10.1109/icbcb55259.2022.9802126","DOIUrl":"https://doi.org/10.1109/icbcb55259.2022.9802126","url":null,"abstract":"Convolutional neural networks (CNNs) can be used to automatically classify the subtypes of renal parenchymal tumors. However, such approaches may overlook the long-range dependencies of features. In this study, we stacked Transformers and CNNs to efficiently capture both long-range dependencies of features and low-level spatial details. The optimal stack layout, the width, and the depth of the networks were determined according to the characteristics of the renal tumors. In addition, we adopted transfer learning for better performance. The experiments conducted on the T2-weighted magnetic resonance (T2W-MR) images from 199 patients presented an 82.9% overall classification accuracy and 0.96 average AUC. The results demonstrate that combining CNN with Transforms is an effective strategy for renal parenchymal tumors diagnosis.","PeriodicalId":429633,"journal":{"name":"2022 10th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127544224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Triple-gate Model for Mechanosensitive Ion Channel Piezo1","authors":"Yu Zhang, Q. Zou","doi":"10.1109/icbcb55259.2022.9802499","DOIUrl":"https://doi.org/10.1109/icbcb55259.2022.9802499","url":null,"abstract":"In this paper, we have developed a Hodgkin-Huxley (HH) -type triple-gate model for mechanosensitive ion channel Piezo1. The model can simulate currents elicited at an invariable saturation pressure (70 mmHg) and at multiple voltages from excised outside-out patches over-expressing Piezo1 in mouse neuroblastoma cells Neuro2A (N2A). The simulation ability of this model is attributed to the introduction of three modifications to the classic HH model. Firstly, varying numbers of gates at depolarized and hyperpolarized voltages are included. Secondly, the steady-state permissive probability of the inactivation gate decreases along with the increasing number of pressure stimuli at hyperpolarized voltages. Finally, the time constant of the activation gate becomes larger as its permissive probability increased at depolarized voltages following hyperpolarized voltages. Parameters are optimized by using the grid search method and Differential Evolution algorithm. The current characteristics at multiple voltages simulated by this model include outward rectification, irreversible desensitized state, and recovery from the desensitized state. The simulated results are in agreement with experimental observations, indicating that this model relates these experimental phenomena to the underlying gate kinetics.","PeriodicalId":429633,"journal":{"name":"2022 10th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123374674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}