Integration of Genomic and Transcriptomic Data to Elucidate Molecular Processes in Babesia divergens

2021 ◽  
pp. 199-215
Author(s):  
Luis Miguel Gonzalez ◽  
Elena Sevilla ◽  
Miguel Fernández-García ◽  
Alejandro Sanchez-Flores ◽  
Estrella Montero
Keyword(s):  
Molecular Processes ◽  
Transcriptomic Data ◽  
Babesia Divergens

Lighting a path: genetic studies pinpoint neurodevelopmental mechanisms in autism and related disorders

2012 ◽  
Vol 14 (3) ◽  
pp. 239-252
Keyword(s):  
Molecular Mechanisms ◽  
Protein Localization ◽  
Regulation Of Gene Expression ◽  
Neuronal Cell ◽  
Mrna Splicing ◽  
Genetic Mutations ◽  
Scaffolding Proteins ◽  
Molecular Processes ◽  
Genetic Studies ◽  
Novel Treatments

In this review, we outline critical molecular processes that have been implicated by discovery of genetic mutations in autism. These mechanisms need to be mapped onto the neurodevelopment step(s) gone awry that may be associated with cause in autism. Molecular mechanisms include: (i) regulation of gene expression; (ii) pre-mRNA splicing; (iii) protein localization, translation, and turnover; (iv) synaptic transmission; (v) cell signaling; (vi) the functions of cytoskeletal and scaffolding proteins; and (vii) the function of neuronal cell adhesion molecules. While the molecular mechanisms appear broad, they may converge on only one of a few steps during neurodevelopment that perturbs the structure, function, and/or plasticity of neuronal circuitry. While there are many genetic mutations involved, novel treatments may need to target only one of few developmental mechanisms.

The future of research with carnivorous plants

2018 ◽  
Author(s):  
Aaron M. Ellison ◽  
Lubomír Adamec
Keyword(s):  
Natural Selection ◽  
Population Biology ◽  
Field Experiments ◽  
Evolutionary Dynamics ◽  
Species Concept ◽  
Intraspecific Variability ◽  
Carnivorous Plants ◽  
Assisted Migration ◽  
Transcriptomic Data ◽  
Phylogenetic Framework

The material presented in the chapters of Carnivorous Plants: Physiology, Ecology, and Evolution together provide a suite of common themes that could provide a framework for increasing progress in understanding carnivorous plants. All speciose genera would benefit from more robust, intra-generic classifications in a phylogenetic framework that uses a unified species concept. As more genomic, proteomic, and transcriptomic data accrue, new insights will emerge regarding trap biochemistry and regulation; interactions with commensals; and the importance of intraspecific variability on which natural selection works. Continued elaboration of field experiments will provide new insights into basic physiology; population biology; plant-animal and plant-microbe relationships; and evolutionary dynamics, all of which will aid conservation efforts and contribute to discussions of assisted migration as the climate continues to change.

scholarly journals Integration of transcriptomic data identifies key hallmark genes in hypertrophic cardiomyopathy

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jing Xu ◽  
Xiangdong Liu ◽  
Qiming Dai
Keyword(s):  
Machine Learning ◽  
Hypertrophic Cardiomyopathy ◽  
Heart Diseases ◽  
Expression Patterns ◽  
Support Vector ◽  
Rna Seq ◽  
Ppi Network ◽  
Learning Methods ◽  
Transcriptomic Data ◽  
Machine Learning Methods

Abstract Background Hypertrophic cardiomyopathy (HCM) represents one of the most common inherited heart diseases. To identify key molecules involved in the development of HCM, gene expression patterns of the heart tissue samples in HCM patients from multiple microarray and RNA-seq platforms were investigated. Methods The significant genes were obtained through the intersection of two gene sets, corresponding to the identified differentially expressed genes (DEGs) within the microarray data and within the RNA-Seq data. Those genes were further ranked using minimum-Redundancy Maximum-Relevance feature selection algorithm. Moreover, the genes were assessed by three different machine learning methods for classification, including support vector machines, random forest and k-Nearest Neighbor. Results Outstanding results were achieved by taking exclusively the top eight genes of the ranking into consideration. Since the eight genes were identified as candidate HCM hallmark genes, the interactions between them and known HCM disease genes were explored through the protein–protein interaction (PPI) network. Most candidate HCM hallmark genes were found to have direct or indirect interactions with known HCM diseases genes in the PPI network, particularly the hub genes JAK2 and GADD45A. Conclusions This study highlights the transcriptomic data integration, in combination with machine learning methods, in providing insight into the key hallmark genes in the genetic etiology of HCM.

scholarly journals Sialic Acid—Modified Nanoparticles—New Approaches in the Glioma Management—Perspective Review

2021 ◽  
Vol 22 (14) ◽  
pp. 7494
Author(s):  
Przemyslaw Wielgat ◽  
Katarzyna Niemirowicz-Laskowska ◽  
Agnieszka Z. Wilczewska ◽  
Halina Car
Keyword(s):  
Sialic Acid ◽  
Clinical Observation ◽  
Malignant Cell ◽  
Cellular Heterogeneity ◽  
Molecular Processes ◽  
Management Perspective ◽  
Therapeutic Tools ◽  
And Function ◽  
Worse Prognosis

The cell surface is covered by a dense and complex network of glycans attached to the membrane proteins and lipids. In gliomas, the aberrant sialylation, as the final stage of glycosylation, is an important regulatory mechanism of malignant cell behavior and correlates with worse prognosis. Better understanding of the role of sialylation in cellular and molecular processes opens a new way in the development of therapeutic tools for human brain tumors. According to the recent clinical observation, the cellular heterogeneity, activity of brain cancer stem cells (BCSCs), immune evasion, and function of the blood–brain barrier (BBB) are attractive targets for new therapeutic strategies. In this review, we summarize the importance of sialic acid-modified nanoparticles in brain tumor progression.

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