지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2022.11
- 수록면
- 1,874 - 1,877 (4page)
이용수
초록· 키워드
오류제보하기
N4-methylcytosine (4mC) is amongst the most significant DNA modifications and is associated with the progression of gene expression, gene differentiation, and cell proliferation. It is essential to locate their alteration sites in the genome sequences in order to understand the biological roles of 4mC. Deep learning has recently gained popularity and is widely used for the identification of 4mC sites. In this study, a convolutional neural network (CNN) based model using CapsuleNet, 4mCPred-Caps, was created to categorize 4mC sites in three different species, Arabidopsis thaliana, Caenorhabditis elegans, and Drosophila melanogaster. Using the benchmark datasets of these species, we assessed the model performance and equate it with the previously available methodologies. We built our model using a single encoding technique called one-hot-encoding along with a special architecture called CapsuleNet. The proposed model acquired an accuracy of 84.8%, 90%, and 88.2% respectively on Arabidopsis thaliana, Caenorhabditis elegans, and Drosophila melanogaster respectively. The outcomes demonstrate that the proposed model surpassed the currently available tools in terms of all assessment parameters. The results collected indicate that the suggested approach can be very beneficial in the area of bioinformatics.
목차
Abstract
1. INTRODUCTION
2. BENCHMARK DATASETS
3. PROPOSED METHODOLOGY
4. EVALUATION METRICS
5. RESULTS
6. CONCLUSIONS
REFERENCES
참고문헌 (0)
참고문헌 신청함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
DNA N4- methylcytosine sites prediction using Convolutional Neural Network
대한전자공학회 학술대회
2020 .08
-
Utilizing Deep Learning Model to Identify DNA N4-Methylcytosine Sites
대한전자공학회 학술대회
2020 .08
-
i4mC-NN: Identification of 4mC sites in Rosaceae Genome Using Neural Network Architecture With Multiple Encoding Schemes
제어로봇시스템학회 국제학술대회 논문집
2022 .11
-
Identification of 4mC modification sites based on ElasticNet and Machine Learning
제어로봇시스템학회 국내학술대회 논문집
2022 .06
-
Identification of m6A modification sites in Arabidopsis thaliana by using eXtreme Gradient Boosting
대한전자공학회 학술대회
2020 .08
-
Direct Electrochemical Measurement of 5-Methylcytosine and Cytosine Using Micro Carbon Electrodes
대한기계학회 춘추학술대회
2019 .11
-
The role of insulin/IGF-1 signaling in the longevity of model invertebrates, C. elegans and D. melanogaster
BMB Reports
2016 .01
-
Predicting DNA N4-Methylctosine Sites in the Mouse Genome Using Convolutional Neural Network
대한전자공학회 학술대회
2021 .11
-
국내 유명 MC들에 대한 음성 특징 분석
한국통신학회 학술대회논문집
2015 .06
-
MC 기법을 이용한 수소 탱크 충전 성능 향상에 관한 연구
한국수소및신에너지학회논문집
2023 .10
-
A Descriptive Convolution Neural Network Model Using Diversify Encoding Formulation to Predict C. elegans Genome
대한전자공학회 학술대회
2020 .08
-
Detecting DNA hydroxymethylation: exploring its role in genome regulation
BMB Reports
2024 .03
-
다중 안테나를 사용하는 이동통신 시스템에서 CNN 기반 송신 안테나 및 MCS 선택
한국통신학회논문지
2023 .09
-
On-the-Fly Estimation Strategy for Uncertainty Propagation in Two-Step Monte Carlo Calculation for Residual Radiation Analysis
Nuclear Engineering and Technology
2016 .06
-
DNA N6-methyladenine Modification Identification in Rice Genome Based on Fusion of Neural Network and Nave Bayes
대한전기학회 학술대회 논문집
2021 .10
-
MCS에 의한 구조물의 지진취약도 곡선 산정 프로그램 개발
한국에너지학회 학술발표회
2024 .10
-
DNA 6mA Sites Identification Using Neural Network and Random Forest in Different Species
대한전기학회 워크샵
2021 .04
-
MCS에 의한 해석기반 기기의 지진취약도 곡선 산정 프로그램 개발
한국에너지학회 학술발표회
2024 .10
-
Simulations of BEAVRS benchmark cycle 2 depletion with MCS/CTF coupling system
Nuclear Engineering and Technology
2020 .01
-
Protective Effect of Curcumin Nanoparticles on Dopaminergic Neuronal System in Caenorhabditis elegans
한국생물공학회 학술대회
2019 .10
이 논문의 저자 정보
최근 본 자료
댓글(0)
0