Debutant iOS app and gene-disease complexities in clinical genomics and precision medicine.

BACKGROUND: The last decade has seen a dramatic increase in the availability of scientific data, where human-related biological databases have grown not only in count but also in volume, posing unprecedented challenges in data storage, processing, analysis, exchange, and curation. Next generation sequencing (NGS) advancements have facilitated and accelerated the process of identifying genetic variations. Adopting NGS with Whole-Genome and RNA sequencing in a diagnostic context has the potential to improve disease-risk detection in support of precision medicine and drug discovery. Several bioinformatics pipelines have been developed to strengthen variant interpretation by efficiently processing and analyzing sequence data, whereas many published results show how genomics data can be proactively incorporated into medical practices and improve utilization of clinical information. To utilize the wealth of genomics and health, there is a crucial need to generate appropriate gene-disease annotation repositories accessed through modern technology. RESULTS: Our focus here is to create a comprehensive database with mobile access to actionable genes and classified diseases, considered the foundation for clinical genomics and precision medicine. We present a publicly available iOS app, PAS-Gen, which invites global users to freely download it on iPhone and iPad devices, quickly adopt its easy to use interface, and search for genes and related diseases. PAS-Gen was developed using Swift, XCODE, and PHP scripting that uses Web and MySQL database servers, which includes over 59,000 protein-coding and non-coding genes, and over 90,000 classified gene-disease associations. PAS-Gen is founded on the clinical and scientific premise that easier healthcare and genomics data sharing will accelerate future medical discoveries. CONCLUSIONS: We present a cutting-edge gene-disease database with a smart phone application, integrating information on classified diseases and related genes. The PAS-Gen app will assist researchers, medical practitioners, and pharmacists by providing a broad and view of genes that may be implicated in the likelihood of developing certain diseases. This tool with accelerate users\u27 abilities to understand the genetic basis of human complex diseases and by assimilating genomic and phenotypic data will support future work to identify gene-specific designer drugs, target precise molecular fingerprints for tumors, suggest appropriate drug therapies, predict individual susceptibility to disease, and diagnose and treat rare illnesses

PGAGP: Predicting pathogenic genes based on adaptive network embedding algorithm

The study of disease-gene associations is an important topic in the field of computational biology. The accumulation of massive amounts of biomedical data provides new possibilities for exploring potential relations between diseases and genes through computational strategy, but how to extract valuable information from the data to predict pathogenic genes accurately and rapidly is currently a challenging and meaningful task. Therefore, we present a novel computational method called PGAGP for inferring potential pathogenic genes based on an adaptive network embedding algorithm. The PGAGP algorithm is to first extract initial features of nodes from a heterogeneous network of diseases and genes efficiently and effectively by Gaussian random projection and then optimize the features of nodes by an adaptive refining process. These low-dimensional features are used to improve the disease-gene heterogenous network, and we apply network propagation to the improved heterogenous network to predict pathogenic genes more effectively. By a series of experiments, we study the effect of PGAGP’s parameters and integrated strategies on predictive performance and confirm that PGAGP is better than the state-of-the-art algorithms. Case studies show that many of the predicted candidate genes for specific diseases have been implied to be related to these diseases by literature verification and enrichment analysis, which further verifies the effectiveness of PGAGP. Overall, this work provides a useful solution for mining disease-gene heterogeneous network to predict pathogenic genes more effectively

Role of precision oncology in type II endometrial and prostate cancers in the African population : global cancer genomics disparities

Precision oncology can be defined as molecular profiling of tumors to identify targetable alterations. Emerging research reports the high mortality rates associated with type II endometrial cancer in black women and with prostate cancer in men of African ancestry. The lack of adequate genetic reference information from the African genome is one of the major obstacles in exploring the benefits of precision oncology in the African context. Whilst external factors such as the geography, environment, health-care access and socio-economic status may contribute greatly towards the disparities observed in type II endometrial and prostate cancers in black populations compared to Caucasians, the contribution of African ancestry to the contribution of genetics to the etiology of these cancers cannot be ignored. Non-coding RNAs (ncRNAs) continue to emerge as important regulators of gene expression and the key molecular pathways involved in tumorigenesis. Particular attention is focused on activated/repressed genes and associated pathways, while the redundant pathways (pathways that have the same outcome or activate the same downstream effectors) are often ignored. However, comprehensive evidence to understand the relationship between type II endometrial cancer, prostate cancer and African ancestry remains poorly understood. The sub-Saharan African (SSA) region has both the highest incidence and mortality of both type II endometrial and prostate cancers. Understanding how the entire transcriptomic landscape of these two reproductive cancers is regulated by ncRNAs in an African cohort may help elucidate the relationship between race and pathological disparities of these two diseases. This review focuses on global disparities in medicine, PCa and ECa. The role of precision oncology in PCa and ECa in the African population will also be discussed.This research was funded by the South African Medical Research Council (SAMRC) Grant No. 23108 and the National Research Foundation (NRF) Grant No. 138139.The South African Medical Research Council and the National Research Foundation.https://www.mdpi.com/journal/ijerphMedical OncologyUrolog

Ensayos sobre ética en la investigación: En el marco de la estancia virtual del XXVIII Verano de la Investigación Científica y Tecnológica del Pacífico. Programa Delfín, 2023.

Ensayos sobre ética en la investigación desarrolladas en el Programa Delfín, 2023. Hecho el depósito legal en la Biblioteca Nacional del Perú N°.2024-01227La ética en la investigación es un pilar fundamental en el desarrollo de la ciencia y la tecnología en nuestra sociedad. Desde la antigüedad, filósofos como Aristóteles han reflexionado sobre los principios morales que guían nuestras acciones y relaciones con el mundo que nos rodea, en el contexto de la investigación, estos compromisos éticos tienen mayor relevancia, ya que influyen en la calidad, confiabilidad e impacto del descubrimiento y progreso científico. Por lo tanto, se convierte en un pilar sobre el que se asienta el conocimiento humano dado que abarca diversos campos de las labores humanas, por lo que su mejora y aumento son esenciales para impulsar el progreso. En esa línea, mejorar la ética en el entorno universitario, surge como una necesidad fundamental en la formación integral de los estudiantes, como futuros investigadores y profesionales, es significativo que comprendan la importancia de actuar éticamente en todas sus actividades científicas. Esta recopilación de ensayos representa el fruto de un proceso educativo en el que distintos estudiantes han elaborado reflexiones y análisis a partir de las conferencias y debates liderados por expertos en el campo de la ética y la integridad académica. A partir de ello, no solo se demuestra el compromiso con la ética en la investigación, sino que también sirven como una herramienta valiosa para fortalecer y difundir las prácticas éticas de investigación universitaria. Esperamos, a través de este esfuerzo colectivo, seguir promoviendo una cultura de ética e integridad en la investigación, contribuyendo así al progreso humano y al bienestar en su conjunto

100 Years of evolving gene-disease complexities and scientific debutants.

It\u27s been over 100 years since the word `gene\u27 is around and progressively evolving in several scientific directions. Time-to-time technological advancements have heavily revolutionized the field of genomics, especially when it\u27s about, e.g. triple code development, gene number proposition, genetic mapping, data banks, gene-disease maps, catalogs of human genes and genetic disorders, CRISPR/Cas9, big data and next generation sequencing, etc. In this manuscript, we present the progress of genomics from pea plant genetics to the human genome project and highlight the molecular, technical and computational developments. Studying genome and epigenome led to the fundamentals of development and progression of human diseases, which includes chromosomal, monogenic, multifactorial and mitochondrial diseases. World Health Organization has classified, standardized and maintained all human diseases, when many academic and commercial online systems are sharing information about genes and linking to associated diseases. To efficiently fathom the wealth of this biological data, there is a crucial need to generate appropriate gene annotation repositories and resources. Our focus has been how many gene-disease databases are available worldwide and which sources are authentic, timely updated and recommended for research and clinical purposes. In this manuscript, we have discussed and compared 43 such databases and bioinformatics applications, which enable users to connect, explore and, if possible, download gene-disease data