scholarly journals Molecular Computing and Bioinformatics

Molecules ◽  
2019 ◽  
Vol 24 (13) ◽  
pp. 2358
Author(s):  
Xin Liang ◽  
Wen Zhu ◽  
Zhibin Lv ◽  
Quan Zou
Keyword(s):  
Organic Chemistry ◽  
Molecular Biology ◽  
Smart Materials ◽  
Close Relationships ◽  
Molecular Computing ◽  
The Core ◽  
Computer Scientists ◽  
Novel Algorithms ◽  
Silicon Based ◽  
Molecular Computers

Molecular computing and bioinformatics are two important interdisciplinary sciences that study molecules and computers. Molecular computing is a branch of computing that uses DNA, biochemistry, and molecular biology hardware, instead of traditional silicon-based computer technologies. Research and development in this area concerns theory, experiments, and applications of molecular computing. The core advantage of molecular computing is its potential to pack vastly more circuitry onto a microchip than silicon will ever be capable of—and to do it cheaply. Molecules are only a few nanometers in size, making it possible to manufacture chips that contain billions—even trillions—of switches and components. To develop molecular computers, computer scientists must draw on expertise in subjects not usually associated with their field, including organic chemistry, molecular biology, bioengineering, and smart materials. Bioinformatics works on the contrary; bioinformatics researchers develop novel algorithms or software tools for computing or predicting the molecular structure or function. Molecular computing and bioinformatics pay attention to the same object, and have close relationships, but work toward different orientations.

Introduction to Molecular Computation

2016 ◽  
pp. 719-743
Author(s):  
Angshuman Bagchi
Keyword(s):  
Molecular Biology ◽  
Biological Membranes ◽  
Computational Techniques ◽  
Molecular Architecture ◽  
Molecular Computation ◽  
Computation Techniques ◽  
Comparative Analyses ◽  
Molecular Logic ◽  
Computer Scientists ◽  
Molecular Computations

The present chapter deals with the topic Molecular Computation. The chapter first defines the basic terminologies associated with the processes. The chapter discusses the basic molecular biology and DNA and membranes. Emphases are given on the structural arrangements of DNA and the molecular architecture of biological membranes. The chapter also focuses on the molecular logic behind the applications of DNA and bimolecular membranes in computations. There are discussions on the current researches that are going on in the field of DNA and membrane computations. There are comparative analyses of the existing computational techniques with molecular computations. There are very few reports that deal with the underlying basics of molecular computation techniques. Thus the chapter may be a first hand guide for researchers interested in the field. The chapter is written for the benefits of both the biologists as well as computer scientists.

Molecular Biology of Protein-Protein Interactions for Computer Scientists

2009 ◽  
pp. 1-13 ◽  
Author(s):  
Christian Schönbach
Keyword(s):  
Molecular Biology ◽  
Protein Interactions ◽  
Wnt Signaling Pathway ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Detection Technology ◽  
Challenges And Opportunities ◽  
Computer Scientists ◽  
Assay Methods

Advances in protein-protein interaction (PPI) detection technology and computational analysis methods have produced numerous PPI networks, whose completeness appears to depend on the extent of data derived from different PPI assay methods and the complexity of the studied organism. Despite the partial nature of human PPI networks, computational data integration and analyses helped to elucidate new interactions and disease pathways. The success of computational analyses considerably depends on PPI data understanding. Exploration of the data and verification of their quality requires basic knowledge of the molecular biology of PPIs and familiarity with the assay methods used to detect PPIs. Both topics are reviewed in this chapter. After introducing various types of PPIs the principles of selected PPI assays are explained and their limitations discussed. Case studies of the Wnt signaling pathway and splice regulation demonstrate some of the challenges and opportunities that arise from assaying and analyzing PPIs. The chapter is concluded with an extrapolation to human systems biology that offers a glimpse into the future of PPI networks.

scholarly journals Nucleic Acid Computing and its Potential to Transform Silicon-Based Technology

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Seth G. Abels ◽  
Emil F. Khisamutdinov
Keyword(s):  
Nucleic Acid ◽  
Logic Gates ◽  
Rna Nanotechnology ◽  
Dna And Rna ◽  
Cellular Machinery ◽  
Living Organisms ◽  
Silicon Based ◽  
Molecular Computers

AbstractMolecular computers have existed on our planet for more than 3.5 billion years. Molecular computing devices, composed of biological substances such as nucleic acids, are responsible for the logical processing of a variety of inputs, creating viable outputs that are key components of the cellular machinery of all living organisms. We have begun to adopt some of the structural and functional knowledge of the cellular apparatus in order to fabricate nucleic-acid-based molecular computers in vitro and in vivo. Nucleic acid computing is directly dependent on advances in DNA and RNA nanotechnology. The field is still emerging and a number of challenges persist. Perhaps the most salient among these is how to translate a variety of nucleic-acid-based logic gates, developed by numerous research laboratories, into the realm of silicon-based computing. This mini-review provides some basic information on the advances in nucleic-acid-based computing and its potential to serve as an alternative that can revolutionize silicon-based technology.

scholarly journals openTSNE: a modular Python library for t-SNE dimensionality reduction and embedding

2019 ◽  
Author(s):  
Pavlin G. Poličar ◽  
Martin Stražar ◽  
Blaž Zupan
Keyword(s):  
Molecular Biology ◽  
Dimensionality Reduction ◽  
Batch Effects ◽  
The Core ◽  
Link Type

AbstractSummaryPoint-based visualisations of large, multi-dimensional data from molecular biology can reveal meaningful clusters. One of the most popular techniques to construct such visualisations is t-distributed stochastic neighbor embedding (t-SNE), for which a number of extensions have recently been proposed to address issues of scalability and the quality of the resulting visualisations. We introduce openTSNE, a modular Python library that implements the core t-SNE algorithm and its extensions. The library is orders of magnitude faster than existing popular implementations, including those from scikit-learn. Unique to openTSNE is also the mapping of new data to existing embeddings, which can surprisingly assist in solving batch effects.AvailabilityopenTSNE is available at https://github.com/pavlin-policar/[email protected], [email protected]

scholarly journals The Core Human Fecal Metabolome

2021 ◽  
Author(s):  
Jacob Haffner ◽  
Mitchelle Katemauswa ◽  
Therese S Kagone ◽  
Ekram Hossain ◽  
David Jacobson ◽  
...  
Keyword(s):  
Molecular Biology ◽  
Human Health ◽  
Metabolomic Analysis ◽  
Behavioral Differences ◽  
Human Phenotype ◽  
The Core ◽  
Hyocholic Acid ◽  
And Behavior

Among the biomolecules at the center of human health and molecular biology is a system of molecules that define the human phenotype known as the metabolome. Through an untargeted metabolomic analysis of samples from Africa and the Americas, the birthplace and the last continental expansion of our species, we present the characterization of the core human fecal metabolome. The majority of detected metabolite features were ubiquitous across populations, despite any geographic, dietary, or behavioral differences. Such shared metabolite features included hyocholic acid and cholesterol. However, any characterization of the core human fecal metabolome is insufficient without exploring the influence of industrialization. Here we show chemical differences along an industrialization gradient, where the degree of industrialization correlates with metabolomic changes. We identified differential metabolite features like leucyl-leucine dipeptides and urobilin as major metabolic correlates of these behavioral shifts. Our results indicate that industrialization significantly influences the human fecal metabolome, but diverse human lifestyles and behavior still maintain a core human fecal metabolome. This study represents the first characterization of the core human fecal metabolome through untargeted analyses of populations along an industrialization gradient.

scholarly journals A Blueprint for the Synthesis and Characterization of Thiolated Graphene

Nanomaterials ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 45
Author(s):  
Maxim K. Rabchinskii ◽  
Victor V. Sysoev ◽  
Sergei A. Ryzhkov ◽  
Ilya A. Eliseyev ◽  
Dina Yu. Stolyarova ◽  
...  
Keyword(s):  
Smart Materials ◽  
Chemical Properties ◽  
Research Community ◽  
Physical And Chemical Properties ◽  
Facile Synthesis ◽  
The Core ◽  
Physical And Chemical ◽  
Significant Attention ◽  
And Chemical Properties

Graphene derivatization to either engineer its physical and chemical properties or overcome the problem of the facile synthesis of nanographenes is a subject of significant attention in the nanomaterials research community. In this paper, we propose a facile and scalable method for the synthesis of thiolated graphene via a two-step liquid-phase treatment of graphene oxide (GO). Employing the core-level methods, the introduction of up to 5.1 at.% of thiols is indicated with the simultaneous rise of the C/O ratio to 16.8. The crumpling of the graphene layer upon thiolation without its perforation is pointed out by microscopic and Raman studies. The conductance of thiolated graphene is revealed to be driven by the Mott hopping mechanism with the sheet resistance values of 2.15 kΩ/sq and dependable on the environment. The preliminary results on the chemiresistive effect of these films upon exposure to ethanol vapors in the mix with dry and humid air are shown. Finally, the work function value and valence band structure of thiolated graphene are analyzed. Taken together, the developed method and findings of the morphology and physics of the thiolated graphene guide the further application of this derivative in energy storage, sensing devices, and smart materials.

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