Sequencing data

The need for intelligent and effective treatment of diseases and the increase in drug design costs have raised drug repurposing as one of the effective strategies in biomedicine. There are various computational methods for drug repurposing, one of which is using transcription signatures, especially single-cell RNA sequencing (scRNAseq) data, which show us a clear and comprehensive view of the inside of the cell to compare the state of disease and health.

11p vishanshan 27-06-2024 1 1   Download

This study proposes an algorithm that includes both PNC frequency and sequence information to identify the predominant provider and estimates the percentage of identified predominant providers. Additionally, differences in travel distances to the predominant and nearest provider are compared.

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T-cell acute lymphoblastic leukemia (T-ALL) is a genetically heterogeneous disease with poor prognosis and inferior outcome. Although multiple studies have been perform on genomics of T-ALL, data from Indian sub-continent is scarce.

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Ovarian cancer (OC) is a complex disease with significant tumor heterogeneity with the worst prognosis and highest mortality among all gynecological cancers. Glycosylation is a specific post-translational modification that plays an important role in tumor progression, immune escape and metastatic spread. The aim of this work was to identify the major glycosylation-related genes (GRGs) in OC and construct an effective GRGs signature to predict prognosis and immunotherapy.

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Ebook "Foundations of computer science" presents the following content: Chapter 1 introduction; chapter 2 recursive functions; chapter 3 notation: estimating costs in the limit; chapter 4 lists; chapter 5 more on lists; chapter 6 sorting; chapter 7 data types and trees; chapter 8 dictionaries and functional arrays; chapter 9 queues and search strategies; chapter 10 functions as values; chapter 11 list functionals; chapter 12 polynomial arithmetic; chapter 13 sequences, or lazy lists; chapter 14 elements of procedural programming; chapter 15 linked data structures.

155p zizaybay1103 29-05-2024 7 2   Download

Ebook Fundamentals of cryptology: A professional reference & interactive tutorial presents the following content: Chapter 1 introduction, chapter 2 classical cryptosystems, chapter 3 shift register sequences, chapter 4 block ciphers, chapter 5 shannon theory, chapter 6 data compression techniques, chapter 7 public-key cryptography, chapter 8 discrete logarithm based systems, chapter 9 RSA based systems, chapter 10 elliptic curves based systems, chapter 11 coding theory based systems, chapter 12 knapsack based systems.

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"The investigation of hot-hand fallacy and gambler’s fallacy in foreign exchange markets" using high frequency foreign exchange market data adopted from the Electronic Brokerage Service (EBS) platform, we explore whether a sequence of continuous trades and reversal trades bring judgment errors associated with processing information from random sequences for institutional investors. We find that, in keeping with hot-hand fallacy, longer spans lead to greater expectations for a continuation.

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In this study, we utilize the genome-wide singlenucleotide polymorphisms (SNPs) data obtained through Multiplexed Inter Simple Sequence Repeat Genotyping by sequencing (MIG-seq) to explore the phylogenetic relationships among Quercus species in Vietnam. The results of this study reveal that all Quercus species in Vietnam belong to subgenus Cerris and the phylogenetic analysis strongly supports the recognition of two infrageneric sections: Quercus and Ilex section for the Vietnamese Quercus.

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We provide the first country record of Opisthotropis durandi Teynié, Lottier, David, Nguyen & Vogel, 2014 from Vietnam based on a single snake specimen from Dien Bien Province. The species previously was only known from the Lao People’s Democratic Republic (Laos). DNA sequence data of a male specimen from Vietnam match those of a specimen of O. durandi from Phongsali province, Laos, and the newly collected individual from Vietnam also corresponds to O. durandi in terms of diagnostic morphological features, except for a slightly higher ventral number (185 versus 177−181).

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This study extracts images from Taekwondo videos and generates skeleton data from frames using the Fast Forward Moving Picture Experts Group (FFMPEG) technique using MoveNet. After that, we use deep learning architectures such as Long Short-Term Memory Networks, Convolutional Long Short-Term Memory, and Longterm Recurrent Convolutional Networks to perform the poses classification tasks in Taegeuk in Jang lessons. This work presents two approaches. The first approach uses a sequence skeleton extracted from the image by Movenet.

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UML has become a standard modeling language because of its programming language independence. UML is used to design software and information systems in the form of common UML diagrams: use case diagrams, class diagrams, sequence diagrams, state diagrams, activity diagrams, component diagrams, and deployment diagrams. The research used case diagrams to design the land price information system functions and class diagrams to design the land price database. Therefore, we use UML language to create a land price information system and land price database for Dan Phuong district, Hanoi city.

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This study reported that the CHI4A gene was isolated from P. mirifica to validate the CHI4A unigenes obtained from the P. mirifica transcriptomic database (data not shown). This work provides more information about the variation and protein profile of the CHI4A gene for further experiments.

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Ebook "Introduction to computational biology: An evolutionary approach" Analysis of molecular sequence data is the main subject of this introduction to computational biology. There are two closely connected aspects to biological sequences: (i) their relative position in the space of all other sequences, and (ii) their movement through this sequence space in evolutionary time. Accordingly, the first part of the book deals with classical methods of sequence analysis: pairwise alignment, exact string matching, multiple alignment, and hidden Markov models.

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Ebook "Models and algorithms for genome evolution" presents a review of the history, current status, and potential future directions of computational biology in molecular evolution. Gathering together the unique insights of an international selection of prestigious researchers, this must-read volume examines the latest developments in the field, the challenges that remain, and the new avenues emerging from the growing influx of sequence data.

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Part 1 of ebook "Software engineering, artificial intelligence, networking and parallel/distributed computing 2011" includes the following main contents: analysis of ISSP environment II survey data using variable clustering; polar transformation system for offline handwritten character recognition; examining QoS guarantees for real-time CBR services in broadband wireless access networks; sin and sigmoid higher order neural networks for data simulations and predictions; a proposal of mouth shapes sequence code for Japanese pronunciation;...

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The present study aims to identify Neofusicoccum isolates collected from lotus with symptoms of dieback, blight, and wilted leaves. Species were identified based on their morphology and comparison of the DNA sequence data for ITS rDNA and β-tubulin (tub-2). The taxonomy and phylogenetic relationships of pathogen isolates were investigated, and their pathogenic abilities were determined.

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Querying cancer genomes at single-cell resolution is expected to provide a powerful framework to understand in detail the dynamics of cancer evolution. However, given the high costs currently associated with single-cell sequencing, together with the inevitable technical noise arising from single-cell genome amplification, cost-effective strategies that maximize the quality of single-cell data are critically needed.

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Large-sequencing cancer genome projects have shown that tumors have thousands of molecular alterations and their frequency is highly heterogeneous. In such scenarios, physicians and oncologists routinely face lists of cancer genomic alterations where only a minority of them are relevant biomarkers to drive clinical decisionmaking.

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A comprehensive understanding of cancer has been furthered with technological improvements and decreasing costs of next-generation sequencing (NGS). However, the complexity of interpreting genomic data is hindering the implementation of high-throughput technologies in the clinical context: increasing evidence on gene–drug interactions complicates the task of assigning clinical significance to genomic variants.

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Comprehensive mutational profiling data now available on all major cancers have led to proposals of novel molecular tumor classifications that modify or replace the established organ- and tissue-based tumor typing. The rationale behind such molecular reclassifications is that genetic alterations underlying cancer pathology predict response to therapy and may therefore offer a more precise view on cancer than histology.

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