Journal ArticleDOI
Prediction of bio-sequence modifications and the associations with diseases.
Chunyan Ao,Liang Yu,Quan Zou +2 more
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TLDR
This review comprehensively summarized the modification site predictors for three different biological sequences and the association with diseases.Abstract:
Modifications of protein, RNA and DNA play an important role in many biological processes and are related to some diseases. Therefore, accurate identification and comprehensive understanding of protein, RNA and DNA modification sites can promote research on disease treatment and prevention. With the development of sequencing technology, the number of known sequences has continued to increase. In the past decade, many computational tools that can be used to predict protein, RNA and DNA modification sites have been developed. In this review, we comprehensively summarized the modification site predictors for three different biological sequences and the association with diseases. The relevant web server is accessible at http://lab.malab.cn/∼acy/PTM_data/ some sample data on protein, RNA and DNA modification can be downloaded from that website.read more
Citations
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Journal ArticleDOI
Distance-based support vector machine to predict DNA N6-methyladenine modification
TL;DR: The outcomes show that the DB-SVM method outperforms the iIM-CNN and csDMA in the prediction of DNA 6mA modification, which are the lastest research onDNA 6mA.
Journal ArticleDOI
PFmulDL: a novel strategy enabling multi-class and multi-label protein function annotation by integrating diverse deep learning methods
Weiqi Xia,Lingyan Zheng,Jiebin Fang,Fengcheng Li,Ying Zhou,Zhenyu Zeng,Bing Zhang,Zhaorong Li,Honglin Li,Feng Zhu +9 more
TL;DR: Li et al. as discussed by the authors proposed PFmulDL, a new protein function annotation strategy, integrating multiple deep learning methods, which is capable of significantly elevating the prediction performance for the rare classes without sacrificing that for the major classes.
Journal ArticleDOI
NmRF: identification of multispecies RNA 2'-O-methylation modification sites from RNA sequences.
Chunyan Ao,Quan Zou,Liang Yu +2 more
TL;DR: Wang et al. as mentioned in this paper constructed a predictor called NmRF based on optimal mixed features and random forest classifier to identify 2'-O-methylation modification sites, which can identify modification sites of multiple species at the same time.
Journal ArticleDOI
Deep-4mCGP: A Deep Learning Approach to Predict 4mC Sites in Geobacter pickeringii by Using Correlation-Based Feature Selection Technique
TL;DR: In the anticipated model, two kinds of feature descriptors, namely, binary and k-mer composition were used to encode the DNA sequences of Geobacter pickeringii.
Journal ArticleDOI
iTTCA-RF: a random forest predictor for tumor T cell antigens.
TL;DR: Li et al. as mentioned in this paper used four types feature encoding methods to build an efficient predictor, including amino acid composition, global protein sequence descriptors and grouped amino acid and peptide composition, and employed a two-step feature selection technique to search for the optimal feature subset.
References
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Journal ArticleDOI
Mass spectrometry-based proteomics
Ruedi Aebersold,Matthias Mann +1 more
TL;DR: The ability of mass spectrometry to identify and, increasingly, to precisely quantify thousands of proteins from complex samples can be expected to impact broadly on biology and medicine.
Journal ArticleDOI
The DNA Damage Response: Making It Safe to Play with Knives
TL;DR: This review will focus on how the DDR controls DNA repair and the phenotypic consequences of defects in these critical regulatory functions in mammals.
Journal ArticleDOI
Direct detection of DNA methylation during single-molecule, real-time sequencing
Benjamin Flusberg,Dale R. Webster,Jessica Lee,Kevin Travers,Eric Olivares,Tyson A. Clark,Jonas Korlach,Stephen Turner +7 more
TL;DR: The direct detection of DNA methylation, without bisulfite conversion, through single-molecule, real-time (SMRT) sequencing is described and is amenable to long read lengths and will likely enable mapping of methylation patterns in even highly repetitive genomic regions.
Journal ArticleDOI
m6A mRNA methylation facilitates resolution of naïve pluripotency toward differentiation
Shay Geula,Sharon Moshitch-Moshkovitz,Dan Dominissini,Abed AlFatah Mansour,Nitzan Kol,Mali Salmon-Divon,Vera Hershkovitz,Eyal Peer,Nofar Mor,Yair S. Manor,Moshe Shay Ben-Haim,Eran Eyal,Sharon Yunger,Yishay Pinto,Diego Jaitin,Sergey Viukov,Yoach Rais,Vladislav Krupalnik,Elad Chomsky,Mirie Zerbib,Itay Maza,Yoav Rechavi,Rada Massarwa,Suhair Hanna,Suhair Hanna,Ido Amit,Erez Y. Levanon,Ninette Amariglio,Ninette Amariglio,Noam Stern-Ginossar,Noa Novershtern,Gideon Rechavi,Jacob H. Hanna +32 more
TL;DR: It is shown that N6-methyladenosine (m6A), a messenger RNA (mRNA) modification present on transcripts of pluripotency factors, drives this transition from the pluripotent to the differentiated state.
Journal ArticleDOI
Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis
Alexander Meissner,Andreas Gnirke,George W. Bell,Bernard Ramsahoye,Eric S. Lander,Rudolf Jaenisch +5 more
TL;DR: Findings indicate random loss rather than specific maintenance of methylation in Dnmt[1kd,3a−/−,3b−/ −] cells, and suggest that random shotgun bisulfite sequencing can be scaled to a genome-wide approach.
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