Liu, Mengya et al. published their research in Briefings in Bioinformatics in 2022 |CAS: 443-72-1

The Article related to dna n methyladenine mol graph rice, dna n6-methyladenine, dna molecular graph feature, smiles, residual block, rice genome, Placeholder for records without volume info and other aspects.Quality Control of N-Methyl-7H-purin-6-amine

Liu, Mengya; Sun, Zhan-Li; Zeng, Zhigang; Lam, Kin-Man published an article in 2022, the title of the article was MGF6mARice: prediction of DNA N6-methyladenine sites in rice by exploiting molecular graph feature and residual block.Quality Control of N-Methyl-7H-purin-6-amine And the article contains the following content:

DNA N6-methyladenine (6mA) is produced by the N6 position of the adenine being methylated, which occurs at the mol. level, and is involved in numerous vital biol. processes in the rice genome. Given the shortcomings of biol. experiments, researchers have developed many computational methods to predict 6mA sites and achieved good performance. However, the existing methods do not consider the occurrence mechanism of 6mA to extract features from the mol. structure. In this paper, a novel deep learning method is proposed by devising DNA mol. graph feature and residual block structure for 6mA sites prediction in rice, named MGF6mARice. Firstly, the DNA sequence is changed into a simplified mol. input line entry system (SMILES) format, which ref lects chem. mol. structure. Secondly, for the mol. structure data, we construct the DNA mol. graph feature based on the principle of graph convolutional network. Then, the residual block is designed to extract higher level, distinguishable features from mol. graph features. Finally, the prediction module is used to obtain the result of whether it is a 6mA site. By means of 10-fold cross-validation, MGF6mARice outperforms the state-of-the-art approaches. Multiple experiments have shown that the mol. graph feature and residual block can promote the performance of MGF6mARice in 6mA prediction. To the best of our knowledge, it is the first time to derive a feature of DNA sequence by considering the chem. mol. structure. We hope that MGF6mARice will be helpful for researchers to analyze 6mA sites in rice. The experimental process involved the reaction of N-Methyl-7H-purin-6-amine(cas: 443-72-1).Quality Control of N-Methyl-7H-purin-6-amine

The Article related to dna n methyladenine mol graph rice, dna n6-methyladenine, dna molecular graph feature, smiles, residual block, rice genome, Placeholder for records without volume info and other aspects.Quality Control of N-Methyl-7H-purin-6-amine

Referemce:
Imidazole – Wikipedia,
Imidazole | C3H4N2 – PubChem

Gao, Chundi et al. published their research in Future Oncology in 2022 |CAS: 443-72-1

The Article related to expression pattern clin relevance regulator cancer type, n6-methyladenine, correlation, pan-cancer, regulatory factor, survival, Placeholder for records without volume info and other aspects.Quality Control of N-Methyl-7H-purin-6-amine

Gao, Chundi; Yu, Haiyang; Li, Huayao; Liu, Cun; Ma, Xiaoran; Zhuang, Jing; Sun, Changgang published an article in 2022, the title of the article was Analysis of the expression patterns and clinical relevance of m6A regulators in 33 cancer types.Quality Control of N-Methyl-7H-purin-6-amine And the article contains the following content:

The role of N6-methyladenine (m6A) RNA methylation in a variety of biol. processes is gradually being revealed. Here, we systematically describe the correlation between the expression pattern of m6A RNA methylation regulatory factors and clin. phenotype, immunity, drug sensitivity, stem cells and prognosis in more than 10,000 samples of 33 types of cancer. The results show that there are significant differences in the expression of 20 m6A RNA methylation regulatory factors in different cancers, and there was a significant correlation with the anal. indicators. In this study, the m6A RNA methylation regulatory factor was found not only to potentially assist in stratifying the prognosis but also to predict or improve the sensitivity of clin. drug therapy. The experimental process involved the reaction of N-Methyl-7H-purin-6-amine(cas: 443-72-1).Quality Control of N-Methyl-7H-purin-6-amine

The Article related to expression pattern clin relevance regulator cancer type, n6-methyladenine, correlation, pan-cancer, regulatory factor, survival, Placeholder for records without volume info and other aspects.Quality Control of N-Methyl-7H-purin-6-amine

Referemce:
Imidazole – Wikipedia,
Imidazole | C3H4N2 – PubChem

Sheng, Yalan et al. published their research in mSphere in 2021 |CAS: 443-72-1

The Article related to tetrahymena environmental stress n6 methyladenine dna modification, 6ma, tetrahymena thermophila, starvation, unicellular eukaryote, Placeholder for records without volume info and other aspects.Application In Synthesis of N-Methyl-7H-purin-6-amine

Sheng, Yalan; Pan, Bo; Wei, Fan; Wang, Yuanyuan; Gao, Shan published an article in 2021, the title of the article was Case study of the response of N6-methyladenine DNA modification to environmental stressors in the unicellular eukaryote Tetrahymena thermophila.Application In Synthesis of N-Methyl-7H-purin-6-amine And the article contains the following content:

Study on the dynamic changes of 6mA under starvation in the unicellular model organism Tetrahymena thermophila. Single-mol., real-time (SMRT) sequencing reveals that DNA 6mA levels in starved cells are significantly reduced, especially sym. 6mA, compared to those in vegetatively growing cells. Despite a global 6mA reduction, the fraction of asym. 6mA with a high methylation level was increased, which might be the driving force for stronger nucleosome positioning in starved cells. Starvation affects expression of many metabolism-related genes, the expression level change of which is associated with the amount of 6mA change, thereby linking 6mA with global transcription and starvation adaptation. These results demonstrated that a regulated 6mA response to environmental cues is evolutionarily conserved in eukaryotes. Increasing evidence indicated that 6mA could respond to environmental stressors in multicellular eukaryotes. As 6mA distribution and function differ significantly in multicellular and unicellular organisms, whether and how 6mA in unicellular eukaryotes responds to environmental stress remains elusive. In the present work, we characterized the dynamic changes of 6mA under starvation in the unicellular model organism Tetrahymena thermophila. Our results provide insights into how Tetrahymena fine-tunes its 6mA level and composition upon starvation, suggesting that a regulated 6mA response to environmental cues is evolutionarily conserved in eukaryotes. The experimental process involved the reaction of N-Methyl-7H-purin-6-amine(cas: 443-72-1).Application In Synthesis of N-Methyl-7H-purin-6-amine

The Article related to tetrahymena environmental stress n6 methyladenine dna modification, 6ma, tetrahymena thermophila, starvation, unicellular eukaryote, Placeholder for records without volume info and other aspects.Application In Synthesis of N-Methyl-7H-purin-6-amine

Referemce:
Imidazole – Wikipedia,
Imidazole | C3H4N2 – PubChem

Goh, Yeek Teck et al. published their research in Nucleic Acids Research in 2020 |CAS: 443-72-1

The Article related to mettl4 m6am transcriptome rna methylation u2snrna premrna splicing, human rna sequence adenosine methylome catalytic site splice site, Placeholder for records without volume info and other aspects.Category: imidazoles-derivatives

Goh, Yeek Teck; Koh, Casslynn W. Q.; Sim, Donald Yuhui; Roca, Xavier; Goh, W. S. Sho published an article in 2020, the title of the article was METTL4 catalyzes m6Am methylation in U2 snRNA to regulate pre-mRNA splicing.Category: imidazoles-derivatives And the article contains the following content:

N6-methylation of 2è·?O-methyladenosine (Am) in RNA occurs in eukaryotic cells to generate N6,2éˆ?O-dimethyladenosine (m6Am). Identification of the methyltransferase responsible for m6Am catalysis has accelerated studies on the function of m6Am in RNA processing. While m6Am is generally found in the first transcribed nucleotide of mRNAs, the modification is also found internally within U2 snRNA. However, the writer required for catalyzing internal m6Am formation had remained elusive. By sequencing transcriptome-wide RNA methylation at single-base-resolution, we identified human METTL4 as the writer that directly methylates Am at U2 snRNA position 30 into m6Am. We found that METTL4 localizes to the nucleus and its conserved methyltransferase catalytic site is required for U2 snRNA methylation. By sequencing human cells with overexpressed Mettl4, we determined METTL4鈥瞫 in vivo target RNA motif specificity. In the absence of Mettl4 in human cells, U2 snRNA lacks m6Am thereby affecting a subset of splicing events that exhibit specific features such as 3éˆ?splice-site weakness and an increase in exon inclusion. These findings suggest that METTL4 methylation of U2 snRNA regulates splicing of specific pre-mRNA transcripts. The experimental process involved the reaction of N-Methyl-7H-purin-6-amine(cas: 443-72-1).Category: imidazoles-derivatives

The Article related to mettl4 m6am transcriptome rna methylation u2snrna premrna splicing, human rna sequence adenosine methylome catalytic site splice site, Placeholder for records without volume info and other aspects.Category: imidazoles-derivatives

Referemce:
Imidazole – Wikipedia,
Imidazole | C3H4N2 – PubChem

Hasan, Mehedi Md et al. published their research in Briefings in Functional Genomics in 2021 |CAS: 443-72-1

The Article related to review dna methyladenine distant sequence, dna n6-methyladenine site, machine learning, prediction model, sequence analysis, web servers, Placeholder for records without volume info and other aspects.Recommanded Product: 443-72-1

Hasan, Mehedi Md; Shoombuatong, Watshara; Kurata, Hiroyuki; Manavalan, Balachandran published an article in 2021, the title of the article was Critical evaluation of web-based DNA N6-methyladenine site prediction tools.Recommanded Product: 443-72-1 And the article contains the following content:

A review. The accurate genome-wide identification of 6mA is a challenging task that leads to understanding the biol. functions. For the last 5 years, a number of bioinformatics approaches and tools for 6mA site prediction have been established, and some of them are easily accessible as web application. Nevertheless, the accurate genome-wide identification of 6mA is still one of the challenging works that lead to understanding the biol. functions. Especially in practical applications, these tools have implemented diverse encoding schemes, machine learning algorithms and feature selection methods, whereas few systematic performance comparisons of 6mA site predictors have been reported. In this review, 11 publicly available 6mA predictors evaluated with seven different species-specific datasets (Arabidopsis thaliana, Tolypocladium, Diospyros lotus, Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans and Escherichia coli). Of those, few species are close homologs, and the remaining datasets are distant sequences. Our independent, validation tests demonstrated that Meta-i6mA and MM-6mAPred models for A. thaliana, Tolypocladium, S. cerevisiae and D. melanogaster achieved excellent overall performance when compared with their counterparts. However, none of the existing methods were suitable for E. coli, C. elegans and D. lotus. A feasibility of the existing predictors is also discussed for the seven species. Our evaluation provides useful guidelines for the development of 6mA site predictors and helps biologists selecting suitable prediction tools. Methylation of DNA N6-methyladenosine (6mA) is a type of epigenetic modification that plays pivotal roles in various biol. processes. The experimental process involved the reaction of N-Methyl-7H-purin-6-amine(cas: 443-72-1).Recommanded Product: 443-72-1

The Article related to review dna methyladenine distant sequence, dna n6-methyladenine site, machine learning, prediction model, sequence analysis, web servers, Placeholder for records without volume info and other aspects.Recommanded Product: 443-72-1

Referemce:
Imidazole – Wikipedia,
Imidazole | C3H4N2 – PubChem

Bataglia, L. et al. published their research in Insect Molecular Biology in 2021 |CAS: 443-72-1

The Article related to apis melipona epigenetic rna modification methyltransferase 28s rrna, apis mellifera, rna methylation, bee, epitranscripitomics, m5c, m6a, Placeholder for records without volume info and other aspects.Electric Literature of 443-72-1

On December 31, 2021, Bataglia, L.; Simoes, Z. L. P.; Nunes, F. M. F. published an article.Electric Literature of 443-72-1 The title of the article was Active genic machinery for epigenetic RNA modifications in bees. And the article contained the following:

Epitranscriptomics is an emerging field of investigation dedicated to the study of post-transcriptional RNA modifications. RNA methylations regulate RNA metabolism and processing, including changes in response to environmental cues. Although RNA modifications are conserved from bacteria to eukaryotes, there is little evidence of an epitranscriptomic pathway in insects. Here we identified genes related to RNA m6A (N6-methyladenine) and m5C (5-methylcytosine) methylation machinery in seven bee genomes (Apis mellifera, Melipona quadrifasciata, Frieseomelitta varia, Eufriesea mexicana, Bombus terrestris, Megachile rotundata and Dufourea novaeangliae). In A. mellifera, we validated the expression of methyltransferase genes and found that the global levels of m6A and m5C measured in the fat body and brain of adult workers differ significantly. Also, m6A levels were differed significantly mainly between the fourth larval instar of queens and workers. Moreover, we found a conserved m5C site in the honeybee 28S rRNA. Taken together, we confirm the existence of epitranscriptomic machinery acting in bees and open avenues for future investigations on RNA epigenetics in a wide spectrum of hymenopteran species. The experimental process involved the reaction of N-Methyl-7H-purin-6-amine(cas: 443-72-1).Electric Literature of 443-72-1

The Article related to apis melipona epigenetic rna modification methyltransferase 28s rrna, apis mellifera, rna methylation, bee, epitranscripitomics, m5c, m6a, Placeholder for records without volume info and other aspects.Electric Literature of 443-72-1

Referemce:
Imidazole – Wikipedia,
Imidazole | C3H4N2 – PubChem

Guo, Dandan et al. published their research in Journal of Chromatography A in 2020 |CAS: 5036-48-6

The Article related to imidazolium stationary phase aminopropylimidazole hilic, hilic, imidazolium group, polar compounds, retention mechanism, stationary phase, Placeholder for records without volume info and other aspects.Application of 5036-48-6

On August 16, 2020, Guo, Dandan; Yang, Chenxi; Qiu, Ruchen; Huang, Shaohua published an article.Application of 5036-48-6 The title of the article was A novel imidazolium bonding stationary phase derived from N-(3-aminopropyl)-imidazole for hydrophilic interaction liquid chromatography. And the article contained the following:

A novel imidazolium bonding method is proposed for the synthesis of hydrophilic interaction liquid chromatog. (HILIC) stationary phases. One obtained stationary phase (SilprAprImCl) was derived from direct reaction between N-(3-aminopropyl)-imidazole and 3-chloropropylated silica gel. Other two materials (SilprAprImBF4 and SilprAprImTf2N) were obtained from SilprAprImCl by ion exchange reaction, resp. FTIR spectroscopy and elemental anal. afforded the proofs of successful imidazolium immobilization and satisfied bonding efficiency. Various polar compounds such as saccharides, nucleosides, and nucleobases were used to evaluate the retention behaviors of these materials in HILIC mode. Different effects from mobile composition, column temperature, imidazolium unite and paired anions (Cl-, BF4-, and Tf2N-) in imidazolium were proved and discussed. Separation mechanism and the role of the imidazolium ions were also studied in mobile phases with different pH. Moreover, chromatog. stability was evaluated by consecutive injections. Finally, the reliability of these stationary phases was demonstrated by the separation of oligosaccharides in real fructooligosaccharides samples. The experimental process involved the reaction of N-(3-Aminopropyl)-imidazole(cas: 5036-48-6).Application of 5036-48-6

The Article related to imidazolium stationary phase aminopropylimidazole hilic, hilic, imidazolium group, polar compounds, retention mechanism, stationary phase, Placeholder for records without volume info and other aspects.Application of 5036-48-6

Referemce:
Imidazole – Wikipedia,
Imidazole | C3H4N2 – PubChem

Liu, Kewei et al. published their research in Molecular Therapy–Nucleic Acids in 2020 |CAS: 443-72-1

The Article related to homo mus rattus convolutional neural network modeling, convolution neural network, m6a, one-hot encoding, spatial specificity of gene expression, Placeholder for records without volume info and other aspects.Safety of N-Methyl-7H-purin-6-amine

On September 4, 2020, Liu, Kewei; Cao, Lei; Du, Pufeng; Chen, Wei published an article.Safety of N-Methyl-7H-purin-6-amine The title of the article was im6A-TS-CNN: Identifying the N6-Methyladenine Site in Multiple Tissues by Using the Convolutional Neural Network. And the article contained the following:

N6-methyladenosine (m6A) is the most abundant post-transcriptional modification and involves a series of important biol. processes. Therefore, accurate detection of the m6A site is very important for revealing its biol. functions and impacts on diseases. Although both exptl. and computational methods have been proposed for identifying m6A sites, few of them are able to detect m6A sites in different tissues. With the consideration of the spatial specificity of m6A modification, it is necessary to develop methods able to detect the m6A site in different tissues. In this work, by using the convolutional neural network (CNN), we proposed a new method, called i.m.6A-TS-CNN, that can identify m6A sites in brain, liver, kidney, heart, and testis of Homo sapiens, Mus musculus, and Rattus norvegicus. In i.m.6A-TS-CNN, the samples were encoded by using the one-hot encoding scheme. The results from both a 5-fold cross-validation test and independent dataset test demonstrate that i.m.6A-TS-CNN is better than the existing method for the same purpose. The experimental process involved the reaction of N-Methyl-7H-purin-6-amine(cas: 443-72-1).Safety of N-Methyl-7H-purin-6-amine

The Article related to homo mus rattus convolutional neural network modeling, convolution neural network, m6a, one-hot encoding, spatial specificity of gene expression, Placeholder for records without volume info and other aspects.Safety of N-Methyl-7H-purin-6-amine

Referemce:
Imidazole – Wikipedia,
Imidazole | C3H4N2 – PubChem

Zeng, Juan et al. published their research in Molecular Therapy–Nucleic Acids in 2021 |CAS: 443-72-1

The Article related to m6a demethylase fto pancreatic cancer pja2 tumorigenesis wnt signaling, n6-methyladenine, pja2, wnt signaling, m6a demethylase fto, pancreatic cancer, Placeholder for records without volume info and other aspects.Synthetic Route of 443-72-1

On September 3, 2021, Zeng, Juan; Zhang, Heying; Tan, Yonggang; Wang, Zhe; Li, Yunwei; Yang, Xianghong published an article.Synthetic Route of 443-72-1 The title of the article was m6A demethylase FTO suppresses pancreatic cancer tumorigenesis by demethylating PJA2 and inhibiting Wnt signaling. And the article contained the following:

Pancreatic cancer is the deadliest malignancy of the digestive system and is the seventh most common cause of cancer-related deaths worldwide. The incidence and mortality of pancreatic cancer continue to increase, and its 5-yr survival rate remains the lowest among all cancers. N6-methyladenine (m6A) is the most abundant reversible RNA modification in various eukaryotic messenger and long noncoding RNAs and plays crucial roles in the occurrence and development of cancers. However, the role of m6A in pancreatic cancer remains unclear. The present study aimed to explore the role of m6A and its regulators in pancreatic cancer and assess its underlying mol. mechanism associated with pancreatic cancer cell proliferation, invasion, and metastasis. Reduced expression of the m6A demethylase, fat mass and obesity-associated protein (FTO), was responsible for the high levels of m6A RNA modification in pancreatic cancer. Moreover, FTO demethylated the m6A modification of praja ring finger ubiquitin ligase 2 (PJA2), thereby reducing its mRNA decay, suppressing Wnt signaling, and ultimately restraining the proliferation, invasion, and metastasis of pancreatic cancer cells. Altogether, this study describes new, potential mol. therapeutic targets for pancreatic cancer that could pave the way to improve patient outcome. The experimental process involved the reaction of N-Methyl-7H-purin-6-amine(cas: 443-72-1).Synthetic Route of 443-72-1

The Article related to m6a demethylase fto pancreatic cancer pja2 tumorigenesis wnt signaling, n6-methyladenine, pja2, wnt signaling, m6a demethylase fto, pancreatic cancer, Placeholder for records without volume info and other aspects.Synthetic Route of 443-72-1

Referemce:
Imidazole – Wikipedia,
Imidazole | C3H4N2 – PubChem

Nguyen, Trinh Trung Duong et al. published their research in Plant Molecular Biology in 2021 |CAS: 443-72-1

The Article related to neural network dna n6 methyladenine, dna n6-methyladenine site prediction, ensemble tree-based algorithms, natural language processing, k-mer embeddings, Placeholder for records without volume info and other aspects.Application of 443-72-1

On December 31, 2021, Nguyen, Trinh Trung Duong; Trinh, Van Ngu; Le, Nguyen Quoc Khanh; Ou, Yu-Yen published an article.Application of 443-72-1 The title of the article was Using k-mer embeddings learned from a Skip-gram based neural network for building a cross-species DNA N6-methyladenine site prediction model. And the article contained the following:

Key message: This study used k-mer embeddings as effective feature to identify DNA N6-Methyladenine sites in plant genomes and obtained improved performance without substantial effort in feature extraction, combination and selection. Identification of DNA N6-methyladenine sites has been a very active topic of computational biol. due to the unavailability of suitable methods to identify them accurately, especially in plants. Substantial results were obtained with a great effort put in extracting, heuristic searching, or fusing a diverse types of features, not to mention a feature selection step. In this study, we regarded DNA sequences as textual information and employed natural language processing techniques to decipher hidden biol. meanings from those sequences. In other words, we considered DNA, the human life book, as a book corpus for training DNA language models. K-mer embeddings then were generated from these language models to be used in machine learning prediction models. Skip-gram neural networks were the base of the language models and ensemble tree-based algorithms were the machine learning algorithms for prediction models. We trained the prediction model on Rosaceae genome dataset and performed a comprehensive test on 3 plant genome datasets. Our proposed method shows promising performance with AUC performance approaching an ideal value on Rosaceae dataset (0.99), a high score on Rice dataset (0.95) and improved performance on Rice dataset while enjoying an elegant, yet efficient feature extraction process. The experimental process involved the reaction of N-Methyl-7H-purin-6-amine(cas: 443-72-1).Application of 443-72-1

The Article related to neural network dna n6 methyladenine, dna n6-methyladenine site prediction, ensemble tree-based algorithms, natural language processing, k-mer embeddings, Placeholder for records without volume info and other aspects.Application of 443-72-1

Referemce:
Imidazole – Wikipedia,
Imidazole | C3H4N2 – PubChem