Research into new methods to identify genes in anonymous genomic sequences has been going on for more than 15 years, Over this period of time, the field has evolved from the designing of programs to identify protein c...
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Research into new methods to identify genes in anonymous genomic sequences has been going on for more than 15 years, Over this period of time, the field has evolved from the designing of programs to identify protein coding regions in compact mitochondrial or bacterial genomes, to the challenge of predicting the detailed organization of multi-exon vertebrate genes. The best program currently available perfectly locates more than 80% of the internal coding exons, and only 5% of the predictions do not overlap a real exon, Given such accuracy, computational methods are indeed very useful;however, they do not alleviate the need for experimental validation. If the performances are satisfactory for the identification of the coding moiety of genes (internal coding exons), the determination of the full extent of the transcript (5' and 3' extremities of the gene) and the location of promoter regions are still unreliable, As the human and mouse genome sequencing projects enter a production mode, the fully automated annotation of megabase-long anonymous genomic sequences is the next big challenge in bioinformatics.
Charge carrier mobility is at the center of organic electronic devices. The strong couplings between electrons and nuclear motions lead to complexities in theoretical description of charge transport, which pose a majo...
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Charge carrier mobility is at the center of organic electronic devices. The strong couplings between electrons and nuclear motions lead to complexities in theoretical description of charge transport, which pose a major challenge for the fundamental understanding and computational design of transport organic materials. This tutorial review describes recent progresses in developing computational tools to assess the carrier mobility in organic molecular semiconductors at the first-principles level. Some rational molecular design strategies for high mobility organic materials are outlined.
A biological network is complex. A group of critical nodes determines the quality and state of such a network. Increasing studies have shown that diseases and biological networks are closely and mutually related and t...
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A biological network is complex. A group of critical nodes determines the quality and state of such a network. Increasing studies have shown that diseases and biological networks are closely and mutually related and that certain diseases are often caused by errors occurring in certain nodes in biological networks. Thus, studying biological networks and identifying critical nodes can help determine the key targets in treating diseases. The problem is how to find the critical nodes in a network efficiently and with low cost. Existing experimental methods in identifying critical nodes generally require much time, manpower and money. Accordingly, many scientists are attempting to solve this problem by researching efficient and low-cost computing methods. To facilitate calculations, biological networks are often modeled as several common networks. In this review, we classify biological networks according to the network types used by several kinds of common computational methods and introduce the computational methods used by each type of network.
Many systems support the design of two-dimensional (2D) regions and three-dimensional (3D) volumes by sweeping a generator contour over spine. Well-established and widely used rendering systems accept high-level bound...
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Many systems support the design of two-dimensional (2D) regions and three-dimensional (3D) volumes by sweeping a generator contour over spine. Well-established and widely used rendering systems accept high-level boundary descriptions of regions and solids but not in the contour-spine form. Hence the swept object design specification must be such as to lend itself to efficient evaluation of a compact and high-level boundary description. In this paper, we identify a sufficiently general class of swept objects and classify the sweep rules. We also present computational methods for directly evaluating the boundary representation which implicitly simulate the sweep process. The boundary is generated as a set of piecewise curves/ surfaces in a compact form suitable for direct input to rendering systems line Postscript(R) in 2D and Renderman(R) in 3D.
The formation of diverse cell types from an invariant set of genes is governed by biochemical and molecular processes that regulate gene activity. A complete understanding of the regulatory mechanisms of gene expressi...
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The formation of diverse cell types from an invariant set of genes is governed by biochemical and molecular processes that regulate gene activity. A complete understanding of the regulatory mechanisms of gene expression is the major function of genomics. computational genomics is a rapidly emerging area for deciphering the regulation of metazoan genes as well as interpreting the results of high-throughput screening. The integration of computer science with biology has expedited molecular modelling and processing of large-scale data inputs such as microarrays, analysis of genomes, transcriptomes and proteomes. Many bioinformaticians have developed various algorithms for predicting transcriptional regulatory mechanisms from the sequence, gene expression and interaction data. This review contains compiled information of various computational methods adopted to dissect gene expression pathways.
The human microbiome is intimately related to cancer biology and plays a vital role in the efficacy of cancer treatments, including immunotherapy. Extraordinary evidence has revealed that several microbes influence tu...
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The human microbiome is intimately related to cancer biology and plays a vital role in the efficacy of cancer treatments, including immunotherapy. Extraordinary evidence has revealed that several microbes influence tumor development through interaction with the host immune system, that is, immuno-oncology- microbiome (IOM). This review focuses on the intratumoral microbiome in IOM and describes the available data and computational methods for discovering biological insights of microbial profiling from host bulk, single-cell, and spatial sequencing data. Critical challenges in data analysis and integration are discussed. Specifically, the microorganisms associated with cancer and cancer treatment in the context of IOM are collected and integrated from the literature. Lastly, we provide our perspectives for future directions in IOM research.
Thanks to latest technical advances in cryo-electron microscopy (cryo-EM), structures of macromolecular complexes (viruses, ribosomes, etc.) are now often obtained at near-atomic resolution. Also, studies of conformat...
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Thanks to latest technical advances in cryo-electron microscopy (cryo-EM), structures of macromolecular complexes (viruses, ribosomes, etc.) are now often obtained at near-atomic resolution. Also, studies of conformational changes of complexes, in connection with their function, are gaining ground. Conformational variability analysis is usually done by classifying images in a number of discrete classes supposedly representing all conformational states present in the specimen. However, discrete classes cannot be meaningfully defined when the conformational change is continuous (the specimen contains a continuum of states instead of a few discrete states). For such cases, first image analysis methods that explicitly consider continuous conformational changes were recently developed. The latest developments in cryo-EM image analysis methods for conformational variability analysis are the focus of this review.
In this article, we review skeletal muscle strain injury with computational methods for strain injury analysis, prevention, and recovery. We first review the theory of muscle strain injury at both the microscopic and ...
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Gordon D, Chen R, Chung S-H. computational methods of Studying the Binding of Toxins From Venomous Animals to Biological Ion Channels: Theory and Applications. Physiol Rev 93: 767-802, 2013;doi:10.1152/physrev.00035.2...
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Gordon D, Chen R, Chung S-H. computational methods of Studying the Binding of Toxins From Venomous Animals to Biological Ion Channels: Theory and Applications. Physiol Rev 93: 767-802, 2013;doi:10.1152/physrev.00035.2012.-The discovery of new drugs that selectively block or modulate ion channels has great potential to provide new treatments for a host of conditions. One promising avenue revolves around modifying or mimicking certain naturally occurring ion channel modulator toxins. This strategy appears to offer the prospect of designing drugs that are both potent and specific. The use of computational modeling is crucial to this endeavor, as it has the potential to provide lower cost alternatives for exploring the effects of new compounds on ion channels. In addition, computational modeling can provide structural information and theoretical understanding that is not easily derivable from experimental results. In this review, we look at the theory and computational methods that are applicable to the study of ion channel modulators. The first section provides an introduction to various theoretical concepts, including force-fields and the statistical mechanics of binding. We then look at various computational techniques available to the researcher, including molecular dynamics, Brownian dynamics, and molecular docking systems. The latter section of the review explores applications of these techniques, concentrating on pore blocker and gating modifier toxins of potassium and sodium channels. After first discussing the structural features of these channels, and their modes of block, we provide an in-depth review of past computational work that has been carried out. Finally, we discuss prospects for future developments in the field.
MicroRNAs (miRNAs) are short RNA molecules that regulate the post-transcriptional expression of their target genes. This regulation may take the form of stable translational or degradation of the target transcript, al...
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MicroRNAs (miRNAs) are short RNA molecules that regulate the post-transcriptional expression of their target genes. This regulation may take the form of stable translational or degradation of the target transcript, although the mechanisms governing the outcome of miRNA-mediated regulation remain largely unknown. While it is becoming clear that miRNAs are core components of gene regulatory networks, elucidating precise roles for each miRNA within these networks will require an accurate means of identifying target genes and assessing the impact of miRNAs on individual targets. Numerous computational methods for predicting targets are currently available. These methods vary widely in their emphasis, accuracy, and ease of use for researchers. This review will focus on a comparison of the available computational methods in animals, with an emphasis on approaches that are informed by experimental analysis of microRNA: target complexes. (C) 2010 Elsevier Ltd. All rights reserved.
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