The Potential Role of Phytochemicals of < em > Juniperus procera < /em > in the Treatment of Ovarian Cancer and the Inhibition of Human Topoisomerase II Alpha Activity
Bioinform Biol Insights. 2024 Apr 25;18:11779322241248904. doi: 10.1177/11779322241248904. eCollection 2024.ABSTRACTA variety of active chemicals found in medicinal plants can be used to develop new medications with few adverse effects. In vitro and in silico analyses were used to evaluate the anticancer properties of Juniperus procera fruit and leaf extracts. Here, we show that the methanolic extract from J procera fruit and leaf extracts inhibits 2 human ovarian cancer cell lines, A2780CP and SKOV-3. The leaf extract demonstrated strong cytotoxicity against A2780CP with an IC50 of 1.2 μg/mL, almost matching the IC50 of ...
Source: Bioinformatics and Biology Insights - April 29, 2024 Category: Bioinformatics Authors: Ateeq A Al-Zahrani Source Type: research
The Novel < em > PTX3 < /em > Variant g.22645332G & gt;T Is Strongly Related to Awassi and Hamdani Sheep Litter Size
Bioinform Biol Insights. 2024 Apr 25;18:11779322241248912. doi: 10.1177/11779322241248912. eCollection 2024.ABSTRACTThe detection of polymorphisms in genes that control livestock reproduction could be highly beneficial for identifying and enhancing economic traits. One of these genes is pentraxin 3 (PTX3), which affects the reproduction of sheep. Therefore, this study investigated whether the variability of the PTX3 gene was related to the litter size of Awassi and Hamdani ewes. A total of 200 ewes (130 Awassi and 70 Hamdani) were used for genomic DNA extraction. Polymerase chain reaction was used to amplify the sequence f...
Source: Bioinformatics and Biology Insights - April 29, 2024 Category: Bioinformatics Authors: Faris S Imran Tahreer M Al-Thuwaini Source Type: research
The Potential Role of Phytochemicals of < em > Juniperus procera < /em > in the Treatment of Ovarian Cancer and the Inhibition of Human Topoisomerase II Alpha Activity
Bioinform Biol Insights. 2024 Apr 25;18:11779322241248904. doi: 10.1177/11779322241248904. eCollection 2024.ABSTRACTA variety of active chemicals found in medicinal plants can be used to develop new medications with few adverse effects. In vitro and in silico analyses were used to evaluate the anticancer properties of Juniperus procera fruit and leaf extracts. Here, we show that the methanolic extract from J procera fruit and leaf extracts inhibits 2 human ovarian cancer cell lines, A2780CP and SKOV-3. The leaf extract demonstrated strong cytotoxicity against A2780CP with an IC50 of 1.2 μg/mL, almost matching the IC50 of ...
Source: Bioinformatics and Biology Insights - April 29, 2024 Category: Bioinformatics Authors: Ateeq A Al-Zahrani Source Type: research
Cauchy hyper-graph Laplacian nonnegative matrix factorization for single-cell RNA-sequencing data analysis
Many important biological facts have been found as single-cell RNA sequencing (scRNA-seq) technology has advanced. With the use of this technology, it is now possible to investigate the connections among indiv... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - April 29, 2024 Category: Bioinformatics Authors: Gao-Fei Wang and Longying Shen Tags: Research Source Type: research
Multi-kernel Learning Fusion Algorithm Based on RNN and GRU for ASD Diagnosis and Pathogenic Brain Region Extraction
AbstractAutism spectrum disorder (ASD) is a complex, severe disorder related to brain development. It impairs patient language communication and social behaviors. In recent years, ASD researches have focused on a single-modal neuroimaging data, neglecting the complementarity between multi-modal data. This omission may lead to poor classification. Therefore, it is important to study multi-modal data of ASD for revealing its pathogenesis. Furthermore, recurrent neural network (RNN) and gated recurrent unit (GRU) are effective for sequence data processing. In this paper, we introduce a novel framework for a Multi-Kernel Learn...
Source: Interdisciplinary Sciences, Computational Life Sciences - April 29, 2024 Category: Bioinformatics Source Type: research
Exploring Novel Fentanyl Analogues Using a Graph-Based Transformer Model
AbstractThe structures of fentanyl and its analogues are easy to be modified and few types have been included in database so far, which allow criminals to avoid the supervision of relevant departments. This paper introduces a molecular graph-based transformer model, which is combined with a data augmentation method based on substructure replacement to generate novel fentanyl analogues. 140,000 molecules were generated, and after a set of screening, 36,799 potential fentanyl analogues were finally obtained. We calculated the molecular properties of 36,799 potential fentanyl analogues. The results showed that the model could...
Source: Interdisciplinary Sciences, Computational Life Sciences - April 29, 2024 Category: Bioinformatics Source Type: research
H-ACO with Consecutive Bases Pairing Constraint for Designing DNA Sequences
AbstractDNA computing is a novel computing method that does not rely on traditional computers. The design of DNA sequences is a crucial step in DNA computing, and the quality of the sequence design directly affects the results of DNA computing. In this paper, a new constraint called the consecutive base pairing constraint is proposed to limit specific base pairings in DNA sequence design. Additionally, to improve the efficiency and capability of DNA sequence design, the Hierarchy-ant colony (H-ACO) algorithm is introduced, which combines the features of multiple algorithms and optimizes discrete numerical calculations. Exp...
Source: Interdisciplinary Sciences, Computational Life Sciences - April 29, 2024 Category: Bioinformatics Source Type: research
CPPLS-MLP: a method for constructing cell-cell communication networks and identifying related highly variable genes based on single-cell sequencing and spatial transcriptomics data
Brief Bioinform. 2024 Mar 27;25(3):bbae198. doi: 10.1093/bib/bbae198.ABSTRACTIn the growth and development of multicellular organisms, the immune processes of the immune system and the maintenance of the organism's internal environment, cell communication plays a crucial role. It exerts a significant influence on regulating internal cellular states such as gene expression and cell functionality. Currently, the mainstream methods for studying intercellular communication are focused on exploring the ligand-receptor-transcription factor and ligand-receptor-subunit scales. However, there is relatively limited research on the a...
Source: Briefings in Bioinformatics - April 28, 2024 Category: Bioinformatics Authors: Tianjiao Zhang Zhenao Wu Liangyu Li Jixiang Ren Ziheng Zhang Guohua Wang Source Type: research
CyclicPepedia: a knowledge base of natural and synthetic cyclic peptides
Brief Bioinform. 2024 Mar 27;25(3):bbae190. doi: 10.1093/bib/bbae190.ABSTRACTCyclic peptides offer a range of notable advantages, including potent antibacterial properties, high binding affinity and specificity to target molecules, and minimal toxicity, making them highly promising candidates for drug development. However, a comprehensive database that consolidates both synthetically derived and naturally occurring cyclic peptides is conspicuously absent. To address this void, we introduce CyclicPepedia (https://www.biosino.org/iMAC/cyclicpepedia/), a pioneering database that encompasses 8744 known cyclic peptides. This re...
Source: Briefings in Bioinformatics - April 28, 2024 Category: Bioinformatics Authors: Lei Liu Liu Yang Suqi Cao Zhigang Gao Bin Yang Guoqing Zhang Ruixin Zhu Dingfeng Wu Source Type: research
scBOL: a universal cell type identification framework for single-cell and spatial transcriptomics data
Brief Bioinform. 2024 Mar 27;25(3):bbae188. doi: 10.1093/bib/bbae188.ABSTRACTMOTIVATION: Over the past decade, single-cell transcriptomic technologies have experienced remarkable advancements, enabling the simultaneous profiling of gene expressions across thousands of individual cells. Cell type identification plays an essential role in exploring tissue heterogeneity and characterizing cell state differences. With more and more well-annotated reference data becoming available, massive automatic identification methods have sprung up to simplify the annotation process on unlabeled target data by transferring the cell type kn...
Source: Briefings in Bioinformatics - April 28, 2024 Category: Bioinformatics Authors: Yuyao Zhai Liang Chen Minghua Deng Source Type: research
DeepKEGG: a multi-omics data integration framework with biological insights for cancer recurrence prediction and biomarker discovery
Brief Bioinform. 2024 Mar 27;25(3):bbae185. doi: 10.1093/bib/bbae185.ABSTRACTDeep learning-based multi-omics data integration methods have the capability to reveal the mechanisms of cancer development, discover cancer biomarkers and identify pathogenic targets. However, current methods ignore the potential correlations between samples in integrating multi-omics data. In addition, providing accurate biological explanations still poses significant challenges due to the complexity of deep learning models. Therefore, there is an urgent need for a deep learning-based multi-omics integration method to explore the potential corre...
Source: Briefings in Bioinformatics - April 28, 2024 Category: Bioinformatics Authors: Wei Lan Haibo Liao Qingfeng Chen Lingzhi Zhu Yi Pan Yi-Ping Phoebe Chen Source Type: research
Modelling the Impact of NETosis During the Initial Stage of Systemic Lupus Erythematosus
Bull Math Biol. 2024 Apr 28;86(6):66. doi: 10.1007/s11538-024-01291-3.ABSTRACTThe development of autoimmune diseases often takes years before clinical symptoms become detectable. We propose a mathematical model for the immune response during the initial stage of Systemic Lupus Erythematosus which models the process of aberrant apoptosis and activation of macrophages and neutrophils. NETosis is a type of cell death characterised by the release of neutrophil extracellular traps, or NETs, containing material from the neutrophil's nucleus, in response to a pathogenic stimulus. This process is hypothesised to contribute to the ...
Source: Bulletin of Mathematical Biology - April 28, 2024 Category: Bioinformatics Authors: Vladimira Suvandjieva Ivanka Tsacheva Marlene Santos Georgios Kararigas Peter Rashkov Source Type: research
Modelling the Impact of NETosis During the Initial Stage of Systemic Lupus Erythematosus
Bull Math Biol. 2024 Apr 28;86(6):66. doi: 10.1007/s11538-024-01291-3.ABSTRACTThe development of autoimmune diseases often takes years before clinical symptoms become detectable. We propose a mathematical model for the immune response during the initial stage of Systemic Lupus Erythematosus which models the process of aberrant apoptosis and activation of macrophages and neutrophils. NETosis is a type of cell death characterised by the release of neutrophil extracellular traps, or NETs, containing material from the neutrophil's nucleus, in response to a pathogenic stimulus. This process is hypothesised to contribute to the ...
Source: Bulletin of Mathematical Biology - April 28, 2024 Category: Bioinformatics Authors: Vladimira Suvandjieva Ivanka Tsacheva Marlene Santos Georgios Kararigas Peter Rashkov Source Type: research
DeepKEGG: a multi-omics data integration framework with biological insights for cancer recurrence prediction and biomarker discovery
Brief Bioinform. 2024 Mar 27;25(3):bbae185. doi: 10.1093/bib/bbae185.ABSTRACTDeep learning-based multi-omics data integration methods have the capability to reveal the mechanisms of cancer development, discover cancer biomarkers and identify pathogenic targets. However, current methods ignore the potential correlations between samples in integrating multi-omics data. In addition, providing accurate biological explanations still poses significant challenges due to the complexity of deep learning models. Therefore, there is an urgent need for a deep learning-based multi-omics integration method to explore the potential corre...
Source: Briefings in Bioinformatics - April 28, 2024 Category: Bioinformatics Authors: Wei Lan Haibo Liao Qingfeng Chen Lingzhi Zhu Yi Pan Yi-Ping Phoebe Chen Source Type: research
scBOL: a universal cell type identification framework for single-cell and spatial transcriptomics data
Brief Bioinform. 2024 Mar 27;25(3):bbae188. doi: 10.1093/bib/bbae188.ABSTRACTMOTIVATION: Over the past decade, single-cell transcriptomic technologies have experienced remarkable advancements, enabling the simultaneous profiling of gene expressions across thousands of individual cells. Cell type identification plays an essential role in exploring tissue heterogeneity and characterizing cell state differences. With more and more well-annotated reference data becoming available, massive automatic identification methods have sprung up to simplify the annotation process on unlabeled target data by transferring the cell type kn...
Source: Briefings in Bioinformatics - April 28, 2024 Category: Bioinformatics Authors: Yuyao Zhai Liang Chen Minghua Deng Source Type: research
