Family DNA_Banking Articles

Home
Ancestry
BioTech
Family
DNA_Banking
Forensic
Medical
Animal
Products
Local
Community
Social Net
Blogs
Search
SiteMap
Admin
Exit
Articles from Springer a leading global scientific publisher of scientific books and journals. - dna banking @ Fri, 30 Jul 2021 at 07:33 AM
Title: - DNA Modification Detection Methods @ 2022-01-01
Abstract
 
Title: - DNA Modification Detection Methods @ 2022-01-01
Abstract
 
Adaptive Machine Learning Algorithm and Analytics of Big Genomic Data for Gene Prediction - Tracking and Preventing Diseases with Artificial Intelligence @ 2022-01-01
Artificial intelligence helps in tracking and preventing diseases. For instance, machine learning algorithms can analyze big genomic data and predict genes, which helps researchers and scientists to gain deep insights about protein-coding genes in viruses that cause certain diseases. To elaborate, prediction of protein-coding genes from the genome of organisms is important to the synthesis of protein and the understating of the regulatory function of the non-coding region. Over the past few years, researchers have developed methods for finding protein-coding genes. Notwithstanding, the recent data explosion in genomics accentuates the need for efficient gene prediction algorithms. This book chapter presents an adaptive naive Bayes-based machine learning (NBML) algorithm to deploy over a cluster of the Apache Spark framework for efficient prediction of genes in the genome of eukaryotic organisms. To evaluate the NBML algorithm on its discovery of the protein-coding genes from the human genome chromosome GRCh37, a confusion matrix was constructed and its results show that NBML led to high specificity, precision and accuracy of 94.01%, 95.04% and 96.02%, respectively. Moreover, the algorithm can be effective for transfer knowledge in new genomic datasets.
 
The Configuration of Smart and Global Mega Cities - Smart Global Megacities @ 2022-01-01
There are about 31 megacities of population size 10 million and above in the universe in 2016 as per UN-Habitat which is likely to be 41 in 2030. These gigantic habitats are significant as it has all the potential to convert into smart and global cities if configured for its sustainability. This creative configuration of megacities to smart and global is the outcomes of the book through city case studies. The vast population, cultural and ecosystem diversity, diverse institutional endowments, supply chains connectivity, global linkages and size of income and expenditure in these megacities creates opportunities for configuring to a smart global city. This chapter tries to understand the title of the book and surveys the growth, development, and distribution across geographic regions. Theories of global cities are studied briefly and finally ends up with broad approaches to configure these megacities to smart and global. In conclusion, the smart global economic community design strategy is detailed out and implemented in Kochi-Kannur megacity study. This chapter serves as a background of several case studies of megacity across many continents in this book.
 
Current State of Methods, Models, and Information Technologies of Genes Expression Profiling Extraction: A Review - Lecture Notes in Computational Intelligence and Decision Making @ 2022-01-01
An application of both the DNA microchips tests or RNA molecules sequencing experiments allows us to form the high-dimensional matrix of genes expressions, values of which are proportional to the number of the appropriate type of genes that matched the respectively investigated sample. In the general instance, the number of genes can achieve tens of thousands of ones. This fact calls the necessity to extract the genes which are able to recognize the examined samples with a high resolvable level. In this review, we analyze the current state of works focused on genes expression profiling extraction based on the application of both single methods and hybrid models. The conducted analysis has allowed us to allocate the advantages and shortcomings of the existing techniques and form the tasks which should be solved in this subject area to improve the objectivity of gene expression profiling extraction considering the type of the investigated samples.
 
This paper aims to understand the development of innovation clusters and hotspots of cutting-edge research in Biotechnology across the world, clusters understood as segments of an innovation system, gathering research institutes, universities, startups, enterprises and funding actors; and hotspots defined as clusters focused on frontier R&D, with economic high potential. The choice of Biotech as study object embeds the special characteristics of this branch of science: long term research with high uncertainty of results, huge funding and few marketable products. The analysis is based on 18 selected tendencies pointed by European Commission as Radical Innovation Breakthroughs and the frequency of these tendencies in several patent databases, focused on which countries are the main applicants since 2005. As a sub product we observed the change, in the studied range of time, of the main axis of Biotech innovation beyond USA, Europe and Japan. The analytical approach is based on literature review and quantitative screening of patent bases.
 
A Study on Deep Learning Predictive Models in Healthcare - Information and Communication Technology for Competitive Strategies (ICTCS 2020) @ 2022-01-01
In spite of large amount of data available today, the healthcare field is facing new challenges in order to automatically detect and diagnose diseases. Deep learning, a branch of artificial intelligence, is growing fast in computer science will provide various tools and techniques to address the challenges in the health care. The rapidly growing fields of predictive analytics and deep learning are playing a major role in the healthcare data practices and research. In this paper, we reviewed the benefits and risks associated with predictive analytics in health care. We studied various deep learning predictive models used in the health care as well as their applications and prominence in healthcare industry. We also summarized applications of different deep learning models and their results.
 
Megalopolis or Mega-city is a new scale that should not be defined by population numbers. We are in a new dimension, a new DNA. In the context of Megalopolis and regions where the scale of the urbanization goes beyond the traditional definition of a Metropolis, defining an effective governance structure and strategies is a challenging yet fundamental goal. Information technology plays a vital role in building the global Megalopolis, as the virtual infrastructure and data allow a city to be strategic at the international scale while advancing inhabitants’ daily life at the local scale. In this chapter we attempt to define the governance strategies in the mega global cities in two steps: first, to trace the dynamics between the various stakeholders in the mega-project that is often complex and less hierarchical and provide a framework where the genome of a Metropolis is evident. The second step emphasizes the importance of the direct relationship between the governance structure and the territorial contexts and intelligences.
 
Market Behavior on the Digital Platform - Prediction and Causality in Econometrics and Related Topics @ 2022-01-01
This paper seeks to develop the theoretical foundation to explain market behavior on the digital platform. To achieve this purpose, the theory of market equilibrium is extended to include both production equilibrium and consumption equilibrium that helps explain the price and the value of a commodity in the market. From this base, the concept of economic surplus is reformulated and market behavior is examined on the digital platform. Findings from this paper reveal that individual behaviors with rational choice are directed towards the production equilibrium or the consumption equilibrium, but the ultimate decisions are relied upon cooperative behaviors towards the status of market equilibrium. This, in turn, provides theoretical foundations to explain market behavior on the digital platform, in which market equilibrium and economic surplus are conducted in the related markets of free goods, advertising services, and economic goods.
 
The Prediction of Anti-cancer Drug Response by Integrating Multi-omics Data - Advances in Intelligent Automation and Soft Computing @ 2022-01-01
Cancer has become one of the most high-incidence diseases in human and the main cause of human death. Due to the heterogeneity of tumors, a treatment plan based solely on the type of cancer may not achieve curative effect as expected. Therefore, predicting the drug response according to the individual characteristics of the patients and formulating a personalized treatment plan are essential to improve the treatment efficiency. In order to solve this problem, we propose a model that uses Convolutional Neural Network and Graph Convolutional Network to extract features from omics data and drug structure data respectively. Finally, the extracted features are integrated and we used a fully connected network to predict the drug response value. To evaluate the reliability of the model, the proposed model is compared with other two models on practical experiments. The experiment results demonstrated that the proposed model gains the best performance. It proves that the proposed model has the potential to play a role in precision oncology.
 
Design and Implementation of Cancer Structural Variants Hotspot Detection and Annotation Software - Advances in Intelligent Automation and Soft Computing @ 2022-01-01
Whole genome sequencing enabled the exploration of genomic structural variants (SVs). However, there is still a lack of software in this field to integrate SVs and functional element database. Here, we propose SVHot, an automated software that detect and annotate SV hotspots. In terms of SV’s hotspot detection, we applies segmentation algorithms to hotspot detection. This work improves the hotspot detection capabilities. In terms of hotspot analysis, we proposes a hotspot annotation algorithm based on cancer types to overcome the shortcomings of existing interval annotation software. Then we develop an annotation database which conclude data of 31 cancer types. SVHots is an integrative software to detect and annotate SVs’ hotspot.
 
Found 11 Articles for dna banking