162,191 research outputs found
RNA修飾部位を予測するための深層学習と機械学習戦略に関する研究
No full text九州工業大学博士（情報工学）1 Introduction| 2 Methods and Materials| 3 Stack-DHUpred| 4 Meta-2OM| 5 GAPred-ac4C| 6 Conclusion| 7 Future Directions| 8 Acknowledgements| 9 List of PublicationsRNA modifications play critical roles in regulating RNA stability, structure, and function, influencing various biological processes. Among nearly 300 known chemical modifications, dihydrouridine (DHU or D) is commonly found in tRNA, mRNA, and snoRNA, which are closely associated with disease pathogenesis and various biological processes in eukaryotes. 2¢-O-methylation (2-OM or Nm) is another widespread RNA modification observed in various RNA types like tRNA, mRNA, rRNA, miRNA, piRNA, and snRNA, which occurs on the ribose sugar of RNA and contributes to stability and translational control. N4-acetylcytidine (ac4C) is another novel and highly conserved chemical modification observed in both eukaryotic and prokaryotic tRNA, rRNA, and mRNA, that is involved in maintaining translational fidelity and enhancing mRNA stability. Understanding these modifications is essential for elucidating post-transcriptional gene regulation and its potential implications in human health and disease. To comprehend its modification mechanisms and potential epigenetic regulation, it is necessary to accurately identify the modification (DHU, 2-OM, ac4C) sites.
Traditional experimental methods for detecting RNA modifications, including DHU, 2-OM, and ac4C, have significantly advanced our understanding of RNA biology. However, these methods are often labor-intensive, technically demanding, time-consuming, and costly, particularly when aiming for single-nucleotide resolution across large transcriptomes. Given these challenges, there is a growing demand for computational prediction models to complement and accelerate the discovery of RNA modification sites. Despite progress, existing computational approaches still face several limitations in prediction performance. For instance, DHU site predictors often suffer from data redundancy due to duplicate samples, limited generalizability to independent datasets, and model overfitting. In the case of 2-OM, many predictors are developed using a single type of RNA (e.g., mRNA or rRNA) or target only specific nucleotide modifications (Am, Gm, Cm, or Um), and are often trained on relatively small datasets. For ac4C, current predictors show low accuracy on independent test datasets. Moreover, several machine learning methods and feature encoding strategies remain unexplored, limiting the full potential of prediction models for these RNA modifications.
To address these challenges, in this study, we proposed three cutting-edge predictors named Stack-DHUpred, Meta-2OM, and GAPred-ac4C, which can accurately identify DHU, 2-OM, and ac4C, respectively. In Stack-DHUpred, we systematically evaluated six classifiers across 11 RNA sequence features, resulting in the development of 66 baseline (single-feature) models. These baseline models were then combined using logistic regression in a stacked ensemble framework. The optimal subset of baseline models was selected to construct the final stacked model, named Stack-DHUpred. This model achieved an accuracy greater than 0.77 and an AUC above 0.87 on the independent dataset, outperforming existing tools on both training and independent datasets. Meta-2OM utilized a meta-learning approach that considered eight conventional machine learning algorithms and eighteen different feature encoding algorithms that cover physicochemical, compositional, position-specific, and natural language processing information. The predicted probabilities of 2-OM sites from the 144 baseline models are then combined and trained using logistic regression to generate the optimal prediction. On the independent test set, Meta-2OM achieved an overall accuracy above 0.87 and AUC above 0.93, demonstrating superior performance compared to the existing predictors. GAPred-ac4C was built by combining probability scores from 120 ML and DL-based single-feature models. Using forward feature selection, a genetic algorithm-based meta-model leveraging six top-performing features from CNNBiGRU, CNNBiLSTM, CNNAtt, and LGBM achieved optimal results. GAPred-ac4C presents the AUC values of 0.893 and 0.902 for training and independent datasets, respectively, which outperformed all existing state-of-the-art methods and demonstrated the superiority of the model. Therefore, the proposed approaches significantly improved the prediction performance, and we believe that these can be extended to other sequence-based function prediction problems, including enhancer prediction, peptide therapeutic function prediction, and post-translational modification sites prediction.
To facilitate its use, two user-friendly web servers and standalone programs have been developed and are freely available at http://kurata35.bio.kyutech.ac.jp/Stack-DHUpred, http://kurata35.bio.kyutech.ac.jp/Meta-2OM/, https://github.com/kuratahiroyuki/Stack- DHUpred, and https://github.com/kuratahiroyuki/Meta-2OM.九州⼯業⼤学博⼠学位論⽂ 学位記番号：情工博甲第412号 学位授与年⽉⽇: 令和7年9⽉25⽇令和7年度doctoral thesi
Chapter 14: MD Anderson Publications and Publication Ethics
No full textDr. Goepfert has served on a number of editorial boards and is keenly interested in the educational dissemination of information critical to cancer research. In this section he talks about some of MD Anderson’s publications and also addresses some controversies with publication. He first raises the ethical issue of how authorship is assigned to a manuscript going out for publication. Today there are guidelines for assigning authorship, but twenty years ago, he explains, some department chairs at MD Anderson reviewed all manuscripts going for publication and insisted on being listed as first author of an article, whether they made any contribution to the research or not. Dr. Goepfert contrasts his own practice of putting his name on a paper only if he has contributed. Dr. Goepfert then shifts subjects and describes several MD Anderson educational publications, beginning with Cancer Bulletin, distributed free to all physicians across Texas.https://openworks.mdanderson.org/mchv_interviewchapters/2010/thumbnail.jp
ESTIMATION OF TREE DIVERSITY AND CARBON STOCK AT THAKURGAON SADAR OF THAKURGAON DISTRICT MD. HARUN OR RASHID
No full textA Thesis
Submitted to the Faculty of Agriculture
Sher-e-Bangla Agricultural University, Dhaka
in partial fulfillment of the requirements
for the degree of
MASTER OF SCIENCE
IN
AGROFORESTRY AND ENVIRONMENTAL SCIENCEThe study was conducted in Thakurgaon sadar upazila of Thakurgaon district. Five villages
namely Paharbhanga, Bhelajan, Palli-Bidyut Bazar, Jamalpur and Akhanagar were
selected. Among randomly selected 60 homesteads, tree diversity per homestead ranged
from 0 to 2.37 using Shannon Wiener index. Twenty-one (21) different tree species under
15 families were identified, among them Betel nut (Areca catechu) was the most
dominating species and the least dominating species was Tetul (Tamarindus indica).
Among small, medium and large home garden categories, the highest mean tree density ha
1
(355.76) was observed from large home garden which showed the maximum mean basal
area (161.82 m
2
ha
-1
), mean tree carbon (100.61 Mg ha
-1
), SOC (28.02 Mg ha
) and tree C
+ soil C stock (181.13 Mg ha
-1
) compared to medium and small homesteads. Among the
selected areas, the large farmers had the highest daily income from homesteads (Tk. 79.37)
followed by medium and small homesteads. Therefore, the results of the study confirmed
that the selected areas can serve as a valuable ecological means in terms of carbon stock
Recommended from our members
Genetically Engineered Microorganisms in Biosensing and Bioremediation
No full textBacteria are ubiquitous microorganisms that exhibit a diverse array of metabolic capabilities and interact with their environment through molecular signaling processes. They have the ability to perceive and respond to several types of molecules, including micronutrients such as iron, zinc, and copper, as well as quorum sensing molecules such as acyl-homoserine lactones (AHLs), autoinducing peptides (AIPs), and autoinducer-2 (AI-2), which are essential for their growth and survival. Additionally, these organisms possess the capability to degrade or transform pollutants, such as heavy metals and organic compounds, into less toxic derivatives. The aforementioned attributes render microorganisms very attractive candidates for the development of biosensors and bioremediation agents. The use of molecular biology techniques in the manipulation of bacterial genomes holds promise for enhancing their functioning and expanding their scope of utility. This dissertation comprises a series of investigations aimed at addressing various challenges related to biosensing and bioremediation. One strategy includes the use of genetically modified whole-cell bacteria capable of biosensing and reporting bioavailable copper levels.Genetically modified microbes, such as Bacillus subtilis, provide a potentially advantageous solution due to its ability to be manipulated to selectively identify copper in soil, thereby obviating the need for soil extractions and high-cost instrumentation. In a separate effort, a number of biosensors were constructed in order to detect several quorum-sensing peptides produced by B. subtilis. In the last part of this dissertation project, B. subtilis endospore display technology was used to successfully express a heterologous enzyme, L-haloacid dehalogenase (HadL), on the surface of endospores. This strategy was used for the aim of environmental bioremediation, with the particular goal of removing halogenated contaminants like 2-haloacids from contaminated water.</p
Chapter 12: The Competing Priorities of Patient Care and Research in the Past and Future of MD Anderson, and the Unsung Hero Clinicians at MD Anderson
No full textDr. Byers gives his perspective on the priority of personal patient care in MD Anderson’s past, Dr. R. Lee Clark’s emphasis on it relative to research, the trend of its deemphasis under subsequent MD Anderson presidents, and the necessity for its reemphasis in the future. Dr. Balch and Dr. Beyers then name the unsung heroes, who “did not publish 50 or 100 papers” or participate in clinical trials, MD Anderson clinicians: Drs. Oscar M. Guillamondegui, William “Bill” MacComb, Edgar “Ed” White, Richard “Dick” G. Martin, Felix N. Rutledge and Douglas E. Johnson. Dr. Byers talks about his pursuit of the “3 Legs of the Stool” (research, publishing, and clinical work), acknowledged the role of publishing to fund MD Anderson research, but emphasized the need for “bench to bed (bedside)” direct application of research to patient care.https://openworks.mdanderson.org/surgeryhist_interviewchapters/1022/thumbnail.jp
RNA修飾部位を予測するための深層学習と機械学習戦略に関する研究
No full text九州工業大学九州工業大学博士学位論文（要旨）学位記番号:情工博甲第412号 学位授与年月日:令和7年9月25日thesi
EFFECT OF BORON ON GROWTH AND YIELD OF FIELD-PEA
No full textA Thesis
submitted to the Faculty of Agriculture,
Sher-e-Bangla Agricultural University, Dhaka
in partial fulfillment of the requirements
for the degree of
MASTER OF SCIENCE
IN
AGRICULTURAL CHEMISTRY
SEMESTER: JAN-JUNE, 2021A field experiment was carried out to find out the effect of boron on growth and yield of
field pea (BARI Motor-3) at the farm of Bangladesh Agricultural Research Institute,
Joydebpur, Gazipur, Bangladesh during the period from November, 2019 to March 2020.
Seven doses of boron including control was considered as treatments viz. T
;
control), T
1
(0.5 kg B ha
-1
), T
2
(1.0 kg B ha
-1
), T
3
(1.5 kg B ha
-1
), T
4
0
(0 kg B ha
(2.0 kg B ha
(2.5 kg B ha
-1
) and T
6
(3.0 kg B ha
-1
). This experiment was laid out in Randomized
Complete Block Design (RCBD) with three replications. All the parameters studied on
growth, yield attributes and yield parameters were significantly affected due to boron
doses. The maximum plant height (107.80 cm) was registered from the treatment T
(3.0
kg B ha
-1
) but the T
3
(1.5 kg B ha
-1
) showed maximum number of branch plant
(4.27),
number of pods plant
-1
(20.53), number of seeds pod
-1
(6.60), 100 seed weight (13.08 g),
seed yield (1732 kg ha
-1
), stover yield (1862 kg ha
-1
), biological yield (3594 kg ha
) and
harvest index (48.27%) whereas the lowest result was obtained from control treatment T
(0 kg B ha
-1
). In terms of nutrients content in field pea seed, significantly highest B
content (33.33 ppm) was recorded from T
but the highest N content (4.81) and Mn
content (102.50 ppm) were achieved from T
5
. Similarly, significantly the highest Zn
content (60.12 ppm) and Fe content (164.30 ppm) was recorded from T
4
whereas the
lowest N, B, Zn, Fe and Mn content were recorded from control treatment (0 kg B ha
).
Regarding P, K, S, Ca and Mg content in field pea seed, non-significant variation was
found among the treatments. So, from the above results, it can be concluded that
application of 1.5 kg B ha
-1
(T
3
) can be treated as best treatment followed by T
(1.0 kg B
ha
-1
) regarding yield performance of field pea (BARI Motor-3).
3
2
-1
-1
6
-1
-1
), T
-1
5
Chapter 02: Recruitment to MD Anderson and Dr. R. Lee Clark, the “Visionary”
No full textDr. Byers relates influences on his decision to join MD Anderson, political considerations in building MD Anderson, and others who joined MD Anderson who worked in, or in concert with, the new field of Head & Neck Surgery. Finally, Dr. Byers gives examples of Dr. R. Lee Clark being a “visionary.”https://openworks.mdanderson.org/surgeryhist_interviewchapters/1012/thumbnail.jp
Chapter 28: Women and Leadership at MD Anderson
No full textDr. Rodriguez provides her views of women and leadership at MD Anderson. She cites statistics in support of her view that “the workforce in medicine is about women.” She stresses that women have to know systems in order to succeed in leadership positions. She offers her view of coming up through the ranks when there were many fewer women and notes that MD Anderson does not have clear processes for filling leadership positions or establishing a pipeline of leaders. She talks about her own strategy for cultivating leadership.https://openworks.mdanderson.org/mchv_interviewchapters/1356/thumbnail.jp
Exact and explicit traveling wave solutions to two nonlinear evolution equations which describe incompressible viscoelastic Kelvin-Voigt fluid
No full textTwo nonlinear evolution equations, namely the Kadomtsev-Petviashvili (KP) equation which describes the dynamics of soliton and nonlinear wave in the field of fluid dynamics, plasma physics and the Oskolkov equation which describes the dynamics of an incompressible visco-elastic Kelvin-Voigt fluid are investigated. We deliberate exact traveling wave solutions, specially kink wave, cusp wave, periodic breather waves and periodic wave solutions of the models applying the modified simple equation method. The solutions can be expressed explicitly. The dynamics of obtained wave solutions are analyzed and illustrated in figures by selecting appropriate parameters. The modified simple equation method is reliable treatment for searching essential nonlinear waves that enrich variety of dynamic models arises in engineering fields
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