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Computational and Structural Biotechnology Journal

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https://www.readbyqxmd.com/read/28316759/fourier-analysis-of-conservation-patterns-in-protein-secondary-structure
#1
Ashok Palaniappan, Eric Jakobsson
Residue conservation is a common observation in alignments of protein families, underscoring positions important in protein structure and function. Though many methods measure the level of conservation of particular residue positions, currently we do not have a way to study spatial oscillations occurring in protein conservation patterns. It is known that hydrophobicity shows spatial oscillations in proteins, which is characterized by computing the hydrophobic moment of the protein domains. Here, we advance the study of moments of conservation of protein families to know whether there might exist spatial asymmetry in the conservation patterns of regular secondary structures...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28289536/dynamic-programming-based-segmentation-in-biomedical-imaging
#2
REVIEW
Kathrin Ungru, Xiaoyi Jiang
Many applications in biomedical imaging have a demand on automatic detection of lines, contours, or boundaries of bones, organs, vessels, and cells. Aim is to support expert decisions in interactive applications or to include it as part of a processing pipeline for automatic image analysis. Biomedical images often suffer from noisy data and fuzzy edges. Therefore, there is a need for robust methods for contour and line detection. Dynamic programming is a popular technique that satisfies these requirements in many ways...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28280526/protein-structure-classification-and-loop-modeling-using-multiple-ramachandran-distributions
#3
Seyed Morteza Najibi, Mehdi Maadooliat, Lan Zhou, Jianhua Z Huang, Xin Gao
Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28228927/computational-approaches-for-revealing-the-structure-of-membrane-transporters-case-study-on-bilitranslocase
#4
REVIEW
Katja Venko, A Roy Choudhury, Marjana Novič
The structural and functional details of transmembrane proteins are vastly underexplored, mostly due to experimental difficulties regarding their solubility and stability. Currently, the majority of transmembrane protein structures are still unknown and this present a huge experimental and computational challenge. Nowadays, thanks to X-ray crystallography or NMR spectroscopy over 3000 structures of membrane proteins have been solved, among them only a few hundred unique ones. Due to the vast biological and pharmaceutical interest in the elucidation of the structure and the functional mechanisms of transmembrane proteins, several computational methods have been developed to overcome the experimental gap...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28228926/antibody-h3-structure-prediction
#5
REVIEW
C Marks, C M Deane
Antibodies are proteins of the immune system that are able to bind to a huge variety of different substances, making them attractive candidates for therapeutic applications. Antibody structures have the potential to be useful during drug development, allowing the implementation of rational design procedures. The most challenging part of the antibody structure to experimentally determine or model is the H3 loop, which in addition is often the most important region in an antibody's binding site. This review summarises the approaches used so far in the pursuit of accurate computational H3 structure prediction...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28228925/what-can-mathematical-modelling-say-about-cho-metabolism-and-protein-glycosylation
#6
REVIEW
Sarah N Galleguillos, David Ruckerbauer, Matthias P Gerstl, Nicole Borth, Michael Hanscho, Jürgen Zanghellini
Chinese hamster ovary cells have been in the spotlight for process optimization in recent years, due to being the major, long established cell factory for the production of recombinant proteins. A deep, quantitative understanding of CHO metabolism and mechanisms involved in protein glycosylation has proven to be attainable through the development of high throughput technologies. Here we review the most notable accomplishments in the field of modelling CHO metabolism and protein glycosylation.
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28217262/the-effects-of-shared-information-on-semantic-calculations-in-the-gene%C3%A2-ontology
#7
Paul W Bible, Hong-Wei Sun, Maria I Morasso, Rasiah Loganantharaj, Lai Wei
The structured vocabulary that describes gene function, the gene ontology (GO), serves as a powerful tool in biological research. One application of GO in computational biology calculates semantic similarity between two concepts to make inferences about the functional similarity of genes. A class of term similarity algorithms explicitly calculates the shared information (SI) between concepts then substitutes this calculation into traditional term similarity measures such as Resnik, Lin, and Jiang-Conrath. Alternative SI approaches, when combined with ontology choice and term similarity type, lead to many gene-to-gene similarity measures...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28179981/deep-assessment-of-genomic-diversity-in-cassava-for-herbicide-tolerance-and-starch-biosynthesis
#8
Jorge Duitama, Lina Kafuri, Daniel Tello, Ana María Leiva, Bernhard Hofinger, Sneha Datta, Zaida Lentini, Ericson Aranzales, Bradley Till, Hernán Ceballos
Cassava is one of the most important food security crops in tropical countries, and a competitive resource for the starch, food, feed and ethanol industries. However, genomics research in this crop is much less developed compared to other economically important crops such as rice or maize. The International Center for Tropical Agriculture (CIAT) maintains the largest cassava germplasm collection in the world. Unfortunately, the genetic potential of this diversity for breeding programs remains underexploited due to the difficulties in phenotypic screening and lack of deep genomic information about the different accessions...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28179980/increasing-european-support-for-neglected-infectious-disease-research
#9
REVIEW
Ole F Olesen, Marit Ackermann
Neglected infectious diseases (NIDs) are a persistent cause of death and disability in low-income countries. Currently available drugs and vaccines are often ineffective, costly or associated with severe side-effects. Although the scale of research on NIDs does not reflect their disease burden, there are encouraging signs that NIDs have begun to attract more political and public attention, which have translated into greater awareness and increased investments in NID research by both public and private donors...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28179979/flexible-gastro-intestinal-endoscopy-clinical-challenges-and-technical-achievements
#10
REVIEW
Niehls Kurniawan, Martin Keuchel
Flexible gastro-intestinal (GI) endoscopy is an integral diagnostic and therapeutic tool in clinical gastroenterology. High quality standards for safety, patients' comfort, and efficiency have already been achieved. Clinical challenges and technical approaches are discussed in this short review. Image enhanced endoscopy for further characterization of mucosal and vascular patterns includes dye-spray or virtual chromoendoscopy. For confocal laser endoscopy, endocytoscopy, and autofluorescence clinical value has not yet been finally evaluated...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28179978/mini-review-in-vitro-metabolic-engineering-for-biomanufacturing-of-high-value-products
#11
REVIEW
Weihua Guo, Jiayuan Sheng, Xueyang Feng
With the breakthroughs in biomolecular engineering and synthetic biology, many valuable biologically active compound and commodity chemicals have been successfully manufactured using cell-based approaches in the past decade. However, because of the high complexity of cell metabolism, the identification and optimization of rate-limiting metabolic pathways for improving the product yield is often difficult, which represents a significant and unavoidable barrier of traditional in vivo metabolic engineering. Recently, some in vitro engineering approaches were proposed as alternative strategies to solve this problem...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28179977/programmable-genome-editing-tools-and-their-regulation-for-efficient-genome-engineering
#12
REVIEW
Tuhin Kumar Guha, Alvan Wai, Georg Hausner
Targeted genome editing has become a powerful genetic tool for studying gene function or for modifying genomes by correcting defective genes or introducing genes. A variety of reagents have been developed in recent years that can generate targeted double-stranded DNA cuts which can be repaired by the error-prone, non-homologous end joining repair system or via the homologous recombination-based double-strand break repair pathway provided a suitable template is available. These genome editing reagents require components for recognizing a specific DNA target site and for DNA-cleavage that generates the double-stranded break...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28179976/biobetters-from-an-integrated-computational-experimental-approach
#13
REVIEW
Serdar Kuyucak, Veysel Kayser
Biobetters are new drugs designed from existing peptide or protein-based therapeutics by improving their properties such as affinity and selectivity for the target epitope, and stability against degradation. Computational methods can play a key role in such design problems-by predicting the changes that are most likely to succeed, they can drastically reduce the number of experiments to be performed. Here we discuss the computational and experimental methods commonly used in drug design problems, focusing on the inverse relationship between the two, namely, the more accurate the computational predictions means the less experimental effort is needed for testing...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28149485/detection-of-side-chain-rearrangements-mediating-the-motions-of-transmembrane-helices-in-molecular-dynamics-simulations-of-g-protein-coupled-receptors
#14
Zied Gaieb, Dimitrios Morikis
Structure and dynamics are essential elements of protein function. Protein structure is constantly fluctuating and undergoing conformational changes, which are captured by molecular dynamics (MD) simulations. We introduce a computational framework that provides a compact representation of the dynamic conformational space of biomolecular simulations. This method presents a systematic approach designed to reduce the large MD simulation spatiotemporal datasets into a manageable set in order to guide our understanding of how protein mechanics emerge from side chain organization and dynamic reorganization...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28138368/investigating-structure-and-dynamics-of-proteins-in-amorphous-phases-using-neutron-scattering
#15
REVIEW
Maria Monica Castellanos, Arnold McAuley, Joseph E Curtis
In order to increase shelf life and minimize aggregation during storage, many biotherapeutic drugs are formulated and stored as either frozen solutions or lyophilized powders. However, characterizing amorphous solids can be challenging with the commonly available set of biophysical measurements used for proteins in liquid solutions. Therefore, some questions remain regarding the structure of the active pharmaceutical ingredient during freezing and drying of the drug product and the molecular role of excipients...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28138367/machine-learning-and-data-mining-methods-in-diabetes-research
#16
REVIEW
Ioannis Kavakiotis, Olga Tsave, Athanasios Salifoglou, Nicos Maglaveras, Ioannis Vlahavas, Ioanna Chouvarda
The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, application of machine learning and data mining methods in biosciences is presently, more than ever before, vital and indispensable in efforts to transform intelligently all available information into valuable knowledge. Diabetes mellitus (DM) is defined as a group of metabolic disorders exerting significant pressure on human health worldwide...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28066534/chagas-disease-research-and-development-is-there-light-at-the-end-of-the-tunnel
#17
REVIEW
Eric Chatelain
Chagas disease, or American trypanosomiasis, is the result of infection by the parasite Trypanosoma cruzi. It is endemic in Latin America, and spreading around the globe due to human migration. Although it was first identified more than a century ago, only two old drugs are available for treatment and a lot of questions related to the disease progression, its pathologies, and not to mention the assessment of treatment efficacy, are subject to debate and remain to be answered. Indeed, the current status of evidence and data available does not allow any absolute statement related to treatment needs and outcome for Chagas patients to be made...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28066533/molecular-mechanism-of-binding-between-17%C3%AE-estradiol-and-dna
#18
Tamsyn A Hilder, Justin M Hodgkiss
Although 17β-estradiol (E2) is a natural molecule involved in the endocrine system, its widespread use in various applications has resulted in its accumulation in the environment and its classification as an endocrine-disrupting molecule. These molecules can interfere with the hormonal system, and have been linked to various adverse effects such as the proliferation of breast cancer. It has been proposed that E2 could contribute to breast cancer by the induction of DNA damage. Mass spectrometry has demonstrated that E2 can bind to DNA but the mechanism by which E2 interacts with DNA has yet to be elucidated...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28066532/matched-molecular-pair-analysis-in-short-algorithms-applications-and-limitations
#19
REVIEW
Christian Tyrchan, Emma Evertsson
Molecular matched pair (MMP) analysis has been used for more than 40 years within molecular design and is still an important tool to analyse potency data and other compound properties. The methods used to find matched pairs range from manual inspection, through supervised methods to unsupervised methods, which are able to find previously unknown molecular pairs. Recent publications demonstrate the value of automatic MMP analysis of publicly available bioactivity databases. The MMP concept has its limitations, but because of its easy to use and intuitive nature, it will remain one of the most important tools in the toolbox of many drug designers...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28018557/a-hybrid-computer-aided-diagnosis-system-for-prediction-of-breast-cancer-recurrence-hpbcr-using-optimized-ensemble-learning
#20
Mohammad R Mohebian, Hamid R Marateb, Marjan Mansourian, Miguel Angel Mañanas, Fariborz Mokarian
Cancer is a collection of diseases that involves growing abnormal cells with the potential to invade or spread to the body. Breast cancer is the second leading cause of cancer death among women. A method for 5-year breast cancer recurrence prediction is presented in this manuscript. Clinicopathologic characteristics of 579 breast cancer patients (recurrence prevalence of 19.3%) were analyzed and discriminative features were selected using statistical feature selection methods. They were further refined by Particle Swarm Optimization (PSO) as the inputs of the classification system with ensemble learning (Bagged Decision Tree: BDT)...
2017: Computational and Structural Biotechnology Journal
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