Log in

Relevant bibliographies by topics / Algorithms- Protein / Journal articles

To see the other types of publications on this topic, follow the link: Algorithms- Protein.

Journal articles on the topic 'Algorithms- Protein'

Author: Grafiati

Published: 6 September 2023

Last updated: 31 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Algorithms- Protein.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Cavanaugh, David, and Krishnan Chittur. "A hydrophobic proclivity index for protein alignments." F1000Research 4 (October 21, 2015): 1097. http://dx.doi.org/10.12688/f1000research.6348.1.

Full text

Abstract:

Sequence alignment algorithms are fundamental to modern bioinformatics. Sequence alignments are widely used in diverse applications such as phylogenetic analysis, database searches for related sequences to aid identification of unknown protein domain structures and classification of proteins and protein domains. Additionally, alignment algorithms are integral to the location of related proteins to secure understanding of unknown protein functions, to suggest the folded structure of proteins of unknown structure from location of homologous proteins and/or by locating homologous domains of known

APA, Harvard, Vancouver, ISO, and other styles

2

Cavanaugh, David, and Krishnan Chittur. "A hydrophobic proclivity index for protein alignments." F1000Research 4 (October 15, 2020): 1097. http://dx.doi.org/10.12688/f1000research.6348.2.

Full text

Abstract:

Sequence alignment algorithms are fundamental to modern bioinformatics. Sequence alignments are widely used in diverse applications such as phylogenetic analysis, database searches for related sequences to aid identification of unknown protein domain structures and classification of proteins and protein domains. Additionally, alignment algorithms are integral to the location of related proteins to secure understanding of unknown protein functions, to suggest the folded structure of proteins of unknown structure from location of homologous proteins and/or by locating homologous domains of known

APA, Harvard, Vancouver, ISO, and other styles

3

Hulianytskyi, Leonid, and Sergii Chornozhuk. "Genetic Algorithm with New Stochastic Greedy Crossover Operator for Protein Structure Folding Problem." Cybernetics and Computer Technologies, no. 2 (July 24, 2020): 19–29. http://dx.doi.org/10.34229/2707-451x.20.2.3.

Full text

Abstract:

Introduction. The spatial protein structure folding is an important and actual problem in biology. Considering the mathematical model of the task, we can conclude that it comes down to the combinatorial optimization problem. Therefore, genetic and mimetic algorithms can be used to find a solution. The article proposes a genetic algorithm with a new greedy stochastic crossover operator, which differs from classical approaches with paying attention to qualities of possible ancestors. The purpose of the article is to describe a genetic algorithm with a new greedy stochastic crossover operator, re

APA, Harvard, Vancouver, ISO, and other styles

4

Begleiter, R., R. El-Yaniv, and G. Yona. "On Prediction Using Variable Order Markov Models." Journal of Artificial Intelligence Research 22 (December 1, 2004): 385–421. http://dx.doi.org/10.1613/jair.1491.

Full text

Abstract:

This paper is concerned with algorithms for prediction of discrete sequences over a finite alphabet, using variable order Markov models. The class of such algorithms is large and in principle includes any lossless compression algorithm. We focus on six prominent prediction algorithms, including Context Tree Weighting (CTW), Prediction by Partial Match (PPM) and Probabilistic Suffix Trees (PSTs). We discuss the properties of these algorithms and compare their performance using real life sequences from three domains: proteins, English text and music pieces. The comparison is made with respect to

APA, Harvard, Vancouver, ISO, and other styles

5

Wang, Caixia, Rongquan Wang, and Kaiying Jiang. "A Method for Detecting Overlapping Protein Complexes Based on an Adaptive Improved FCM Clustering Algorithm." Mathematics 13, no. 2 (2025): 196. https://doi.org/10.3390/math13020196.

Full text

Abstract:

A protein complex can be regarded as a functional module developed by interacting proteins. The protein complex has attracted significant attention in bioinformatics as a critical substance in life activities. Identifying protein complexes in protein–protein interaction (PPI) networks is vital in life sciences and biological activities. Therefore, significant efforts have been made recently in biological experimental methods and computing methods to detect protein complexes accurately. This study proposed a new method for PPI networks to facilitate the processing and development of the followi

APA, Harvard, Vancouver, ISO, and other styles

6

Wang, Derui, and Jingyu Hou. "Explore the hidden treasure in protein–protein interaction networks — An iterative model for predicting protein functions." Journal of Bioinformatics and Computational Biology 13, no. 05 (2015): 1550026. http://dx.doi.org/10.1142/s0219720015500262.

Full text

Abstract:

Protein–protein interaction networks constructed by high throughput technologies provide opportunities for predicting protein functions. A lot of approaches and algorithms have been applied on PPI networks to predict functions of unannotated proteins over recent decades. However, most of existing algorithms and approaches do not consider unannotated proteins and their corresponding interactions in the prediction process. On the other hand, algorithms which make use of unannotated proteins have limited prediction performance. Moreover, current algorithms are usually one-off predictions. In this

APA, Harvard, Vancouver, ISO, and other styles

7

Moschopoulos, Charalampos, Grigorios Beligiannis, Spiridon Likothanassis, and Sophia Kossida. "Using a Genetic Algorithm and Markov Clustering on Protein–Protein Interaction Graphs." International Journal of Systems Biology and Biomedical Technologies 1, no. 2 (2012): 35–47. http://dx.doi.org/10.4018/ijsbbt.2012040103.

Full text

Abstract:

In this paper, a Genetic Algorithm is applied on the filter of the Enhanced Markov Clustering algorithm to optimize the selection of clusters having a high probability to represent protein complexes. The filter was applied on the results (obtained by experiments made on five different yeast datasets) of three different algorithms known for their efficiency on protein complex detection through protein interaction graphs. The results are compared with three popular clustering algorithms, proving the efficiency of the proposed method according to metrics such as successful prediction rate and geo

APA, Harvard, Vancouver, ISO, and other styles

8

Khatami, Mohammad Hassan, Udson C. Mendes, Nathan Wiebe, and Philip M. Kim. "Gate-based quantum computing for protein design." PLOS Computational Biology 19, no. 4 (2023): e1011033. http://dx.doi.org/10.1371/journal.pcbi.1011033.

Full text

Abstract:

Protein design is a technique to engineer proteins by permuting amino acids in the sequence to obtain novel functionalities. However, exploring all possible combinations of amino acids is generally impossible due to the exponential growth of possibilities with the number of designable sites. The present work introduces circuits implementing a pure quantum approach, Grover’s algorithm, to solve protein design problems. Our algorithms can adjust to implement any custom pair-wise energy tables and protein structure models. Moreover, the algorithm’s oracle is designed to consist of only adder func

APA, Harvard, Vancouver, ISO, and other styles

9

Shirmohammady, Naeem, Habib Izadkhah, and Ayaz Isazadeh. "PPI-GA: A Novel Clustering Algorithm to Identify Protein Complexes within Protein-Protein Interaction Networks Using Genetic Algorithm." Complexity 2021 (March 25, 2021): 1–14. http://dx.doi.org/10.1155/2021/2132516.

Full text

Abstract:

Comprehensive analysis of proteins to evaluate their genetic diversity, study their differences, and respond to the tensions is the main subject of an interdisciplinary field of study called proteomics. The main objective of the proteomics is to detect and quantify proteins and study their post-translational modifications and interactions using protein chemistry, bioinformatics, and biology. Any disturbance in proteins interactive network can act as a source for biological disorders and various diseases such as Alzheimer and cancer. Most current computational methods for discovering protein co

APA, Harvard, Vancouver, ISO, and other styles

10

Niazi, Sarfaraz K., Zamara Mariam, and Rehan Z. Paracha. "Limitations of Protein Structure Prediction Algorithms in Therapeutic Protein Development." BioMedInformatics 4, no. 1 (2024): 98–112. http://dx.doi.org/10.3390/biomedinformatics4010007.

Full text

Abstract:

The three-dimensional protein structure is pivotal in comprehending biological phenomena. It directly governs protein function and hence aids in drug discovery. The development of protein prediction algorithms, such as AlphaFold2, ESMFold, and trRosetta, has given much hope in expediting protein-based therapeutic discovery. Though no study has reported a conclusive application of these algorithms, the efforts continue with much optimism. We intended to test the application of these algorithms in rank-ordering therapeutic proteins for their instability during the pre-translational modification

APA, Harvard, Vancouver, ISO, and other styles

11

Dandekar, Thomas, and Patrick Argos. "Potential of genetic algorithms in protein folding and protein engineering simulations." "Protein Engineering, Design and Selection" 5, no. 7 (1992): 637–45. http://dx.doi.org/10.1093/protein/5.7.637.

Full text

APA, Harvard, Vancouver, ISO, and other styles

12

Brown, Michael Scott, Tommy Bennett, and James A. Coker. "Niche Genetic Algorithms are better than traditional Genetic Algorithms for de novo Protein Folding." F1000Research 3 (October 7, 2014): 236. http://dx.doi.org/10.12688/f1000research.5412.1.

Full text

Abstract:

Here we demonstrate that Niche Genetic Algorithms (NGA) are better at computing de novo protein folding than traditional Genetic Algorithms (GA). Previous research has shown that proteins can fold into their active forms in a limited number of ways; however, predicting how a set of amino acids will fold starting from the primary structure is still a mystery. GAs have a unique ability to solve these types of scientific problems because of their computational efficiency. Unfortunately, GAs are generally quite poor at solving problems with multiple optima. However, there is a special group of GAs

APA, Harvard, Vancouver, ISO, and other styles

13

DERONNE, KEVIN W., and GEORGE KARYPIS. "EFFECTIVE OPTIMIZATION ALGORITHMS FOR FRAGMENT-ASSEMBLY BASED PROTEIN STRUCTURE PREDICTION." Journal of Bioinformatics and Computational Biology 05, no. 02a (2007): 335–52. http://dx.doi.org/10.1142/s0219720007002618.

Full text

Abstract:

Despite recent developments in protein structure prediction, an accurate new fold prediction algorithm remains elusive. One of the challenges facing current techniques is the size and complexity of the space containing possible structures for a query sequence. Traditionally, to explore this space fragment assembly approaches to new fold prediction have used stochastic optimization techniques. Here, we examine deterministic algorithms for optimizing scoring functions in protein structure prediction. Two previously unused techniques are applied to the problem, called the Greedy algorithm and the

APA, Harvard, Vancouver, ISO, and other styles

14

Gainza, Pablo, Hunter M. Nisonoff, and Bruce R. Donald. "Algorithms for protein design." Current Opinion in Structural Biology 39 (August 2016): 16–26. http://dx.doi.org/10.1016/j.sbi.2016.03.006.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

Lappe, M., and L. Holm. "Algorithms for protein interaction networks." Biochemical Society Transactions 33, no. 3 (2005): 530–34. http://dx.doi.org/10.1042/bst0330530.

Full text

Abstract:

The functional characterization of all genes and their gene products is the main challenge of the postgenomic era. Recent experimental and computational techniques have enabled the study of interactions among all proteins on a large scale. In this paper, approaches will be presented to exploit interaction information for the inference of protein structure, function, signalling pathways and ultimately entire interactomes. Interaction networks can be modelled as graphs, showing the operation of gene function in terms of protein interactions. Since the architecture of biological networks differs

APA, Harvard, Vancouver, ISO, and other styles

16

Arriagada, Mauricio, and Aleksandar Poleksic. "On the Difference in Quality between Current Heuristic and Optimal Solutions to the Protein Structure Alignment Problem." BioMed Research International 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/459248.

Full text

Abstract:

The importance of pairwise protein structural comparison in biomedical research is fueling the search for algorithms capable of finding more accurate structural match of two input proteins in a timely manner. In recent years, we have witnessed rapid advances in the development of methods for approximate and optimal solutions to the protein structure matching problem. Albeit slow, these methods can be extremely useful in assessing the accuracy of more efficient, heuristic algorithms. We utilize a recently developed approximation algorithm for protein structure matching to demonstrate that a dee

APA, Harvard, Vancouver, ISO, and other styles

17

CHUA, HON NIAN, KANG NING, WING-KIN SUNG, HON WAI LEONG, and LIMSOON WONG. "USING INDIRECT PROTEIN–PROTEIN INTERACTIONS FOR PROTEIN COMPLEX PREDICTION." Journal of Bioinformatics and Computational Biology 06, no. 03 (2008): 435–66. http://dx.doi.org/10.1142/s0219720008003497.

Full text

Abstract:

Protein complexes are fundamental for understanding principles of cellular organizations. As the sizes of protein–protein interaction (PPI) networks are increasing, accurate and fast protein complex prediction from these PPI networks can serve as a guide for biological experiments to discover novel protein complexes. However, it is not easy to predict protein complexes from PPI networks, especially in situations where the PPI network is noisy and still incomplete. Here, we study the use of indirect interactions between level-2 neighbors (level-2 interactions) for protein complex prediction. We

APA, Harvard, Vancouver, ISO, and other styles

18

Ruiz Echartea, Maria Elisa, Isaure Chauvot de Beauchêne, and David W. Ritchie. "EROS-DOCK: protein–protein docking using exhaustive branch-and-bound rotational search." Bioinformatics 35, no. 23 (2019): 5003–10. http://dx.doi.org/10.1093/bioinformatics/btz434.

Full text

Abstract:

Abstract Motivation Protein–protein docking algorithms aim to predict the 3D structure of a binary complex using the structures of the individual proteins. This typically involves searching and scoring in a 6D space. Many docking algorithms use FFT techniques to exhaustively cover the search space and to accelerate the scoring calculation. However, FFT docking results often depend on the initial protein orientations with respect to the Fourier sampling grid. Furthermore, Fourier-transforming a physics-base force field can involve a serious loss of precision. Results Here, we present EROS-DOCK,

APA, Harvard, Vancouver, ISO, and other styles

19

Sánchez-Hernández, Juan P., Juan Frausto-Solís, Juan J. González-Barbosa, Diego A. Soto-Monterrubio, Fanny G. Maldonado-Nava, and Guadalupe Castilla-Valdez. "A Peptides Prediction Methodology for Tertiary Structure Based on Simulated Annealing." Mathematical and Computational Applications 26, no. 2 (2021): 39. http://dx.doi.org/10.3390/mca26020039.

Full text

Abstract:

The Protein Folding Problem (PFP) is a big challenge that has remained unsolved for more than fifty years. This problem consists of obtaining the tertiary structure or Native Structure (NS) of a protein knowing its amino acid sequence. The computational methodologies applied to this problem are classified into two groups, known as Template-Based Modeling (TBM) and ab initio models. In the latter methodology, only information from the primary structure of the target protein is used. In the literature, Hybrid Simulated Annealing (HSA) algorithms are among the best ab initio algorithms for PFP; G

APA, Harvard, Vancouver, ISO, and other styles

20

SOHAEE, NASSIM, and CHRISTIAN V. FORST. "IDENTIFICATION OF FUNCTIONAL MODULES IN A PPI NETWORK BY BOUNDED DIAMETER CLUSTERING." Journal of Bioinformatics and Computational Biology 08, no. 06 (2010): 929–43. http://dx.doi.org/10.1142/s0219720010005221.

Full text

Abstract:

Dense subgraphs of Protein–Protein Interaction (PPI) graphs are assumed to be potential functional modules and play an important role in inferring the functional behavior of proteins. Increasing amount of available PPI data implies a fast, accurate approach of biological complex identification. Therefore, there are different models and algorithms in identifying functional modules. This paper describes a new graph theoretic clustering algorithm that detects densely connected regions in a large PPI graph. The method is based on finding bounded diameter subgraphs around a seed node. The algorithm

APA, Harvard, Vancouver, ISO, and other styles

21

Minul, Vijayakumar, and George Joby. "Classification of Hot Spots using XGBoost and LightGBM Algorithms." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 5 (2020): 722–24. https://doi.org/10.35940/ijeat.E9459.069520.

Full text

Abstract:

Protein-Protein Interactions referred as PPIs perform significant role in biological functions like cell metabolism, immune response, signal transduction etc. Hot spots are small fractions of residues in interfaces and provide substantial binding energy in PPIs. Therefore, identification of hot spots is important to discover and analyze molecular medicines and diseases. The current strategy, alanine scanning isn't pertinent to enormous scope applications since the technique is very costly and tedious. The existing computational methods are poor in classification performance as well as accu

APA, Harvard, Vancouver, ISO, and other styles

22

Chen, Ye. "Advancements and Applications of Protein Structure Prediction Algorithms." Theoretical and Natural Science 74, no. 1 (2024): 119–27. https://doi.org/10.54254/2753-8818/2024.la18791.

Full text

Abstract:

Protein structure prediction serves as a foundational aspect of molecular biology, where computational advancements have recently propelled significant increases in prediction accuracy. This paper evaluates traditional protein structure prediction methods, including homology modeling, threading, and Ab Initio techniques, emphasizing the inherent challenges these methods face in accurately modeling novel and highly flexible proteins. With the advent of AI-based models, particularly AlphaFold, the landscape of protein structure prediction has undergone a transformative shift. AlphaFold integrate

APA, Harvard, Vancouver, ISO, and other styles

23

IBRAHEEM JABBAR, NAHLA. "Automate Secondary Protein Structure Prediction based on spatial information." Kerbala Journal for Engineering Sciences 4, no. 1 (2024): 15–24. https://doi.org/10.63463/kjes1112.

Full text

Abstract:

This study discusses the prediction of secondary structure protein from features of amino acid images. We define a predication algorithm depending on the spatial information of amino acid sequences. Algorithm A and algorithm B are applied to extract spatial information for clustering types of amino acids in three states: helix(H), strand(E), and coil(C). The accuracy of clustering depends on the improvement of algorithm B and the parameters of algorithms A and B. We apply a novel approach to spatial information extraction from primary protein structure to predicate three states of secondary pr

APA, Harvard, Vancouver, ISO, and other styles

24

DUKKA BAHADUR, K. C., ETSUJI TOMITA, JUN'ICHI SUZUKI, and TATSUYA AKUTSU. "PROTEIN SIDE-CHAIN PACKING PROBLEM: A MAXIMUM EDGE-WEIGHT CLIQUE ALGORITHMIC APPROACH." Journal of Bioinformatics and Computational Biology 03, no. 01 (2005): 103–26. http://dx.doi.org/10.1142/s0219720005000904.

Full text

Abstract:

"Protein Side-chain Packing" has an ever-increasing application in the field of bio-informatics, dating from the early methods of homology modeling to protein design and to the protein docking. However, this problem is computationally known to be NP-hard. In this regard, we have developed a novel approach to solve this problem using the notion of a maximum edge-weight clique. Our approach is based on efficient reduction of protein side-chain packing problem to a graph and then solving the reduced graph to find the maximum clique by applying an efficient clique finding algorithm developed by ou

APA, Harvard, Vancouver, ISO, and other styles

25

Shen, Li, Jian Zhang, Fang Wang, and Kai Liu. "Predicting Essential Proteins Based on Integration of Local Fuzzy Fractal Dimension and Subcellular Location Information." Genes 13, no. 2 (2022): 173. http://dx.doi.org/10.3390/genes13020173.

Full text

Abstract:

Essential proteins are indispensable to cells’ survival and development. Prediction and analysis of essential proteins are crucial for uncovering the mechanisms of cells. With the help of computer science and high-throughput technologies, forecasting essential proteins by protein–protein interaction (PPI) networks has become more efficient than traditional approaches (expensive experimental methods are generally used). Many computational algorithms were employed to predict the essential proteins; however, they have various restrictions. To improve the prediction accuracy, by introducing the Lo

APA, Harvard, Vancouver, ISO, and other styles

26

Dunham, Brandan, and Madhavi K. Ganapathiraju. "Benchmark Evaluation of Protein–Protein Interaction Prediction Algorithms." Molecules 27, no. 1 (2021): 41. http://dx.doi.org/10.3390/molecules27010041.

Full text

Abstract:

Protein–protein interactions (PPIs) perform various functions and regulate processes throughout cells. Knowledge of the full network of PPIs is vital to biomedical research, but most of the PPIs are still unknown. As it is infeasible to discover all of them experimentally due to technical and resource limitations, computational prediction of PPIs is essential and accurately assessing the performance of algorithms is required before further application or translation. However, many published methods compose their evaluation datasets incorrectly, using a higher proportion of positive class data

APA, Harvard, Vancouver, ISO, and other styles

27

Vreven, Thom, Howook Hwang, and Zhiping Weng. "Exploring Angular Distance in Protein-Protein Docking Algorithms." PLoS ONE 8, no. 2 (2013): e56645. http://dx.doi.org/10.1371/journal.pone.0056645.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

YE, JIEPING, RAVI JANARDAN, and SONGTAO LIU. "PAIRWISE PROTEIN STRUCTURE ALIGNMENT BASED ON AN ORIENTATION-INDEPENDENT BACKBONE REPRESENTATION." Journal of Bioinformatics and Computational Biology 02, no. 04 (2004): 699–717. http://dx.doi.org/10.1142/s021972000400082x.

Full text

Abstract:

Determining structural similarities between proteins is an important problem since it can help identify functional and evolutionary relationships. In this paper, an algorithm is proposed to align two protein structures. Given the protein backbones, the algorithm finds a rigid motion of one backbone onto the other such that large substructures are matched. The algorithm uses a representation of the backbones that is independent of their relative orientations in space and applies dynamic programming to this representation to compute an initial alignment, which is then refined iteratively. Experi

APA, Harvard, Vancouver, ISO, and other styles

29

Wang, Fengjuan, Cheng Xu, Shufeng Jiang, and Fengxia Xu. "Application of improved intelligent ant colony algorithm in protein folding prediction." Journal of Algorithms & Computational Technology 14 (January 2020): 174830262094141. http://dx.doi.org/10.1177/1748302620941411.

Full text

Abstract:

While the single ant colony algorithm and the fish swarm algorithm have many advantages, they also have various shortcomings. After analyzing the advantages and disadvantages of the ant colony algorithm and the fish swarm algorithm, this paper uses the complementary principle of the two algorithms to effectively fuse the two population intelligent algorithms. The improved swarm intelligence algorithm is applied to the well-considered protein folding prediction problem, and the simplified protein structure Toy model is verified, and the ideal results are obtained. The improved algorithm enhance

APA, Harvard, Vancouver, ISO, and other styles

30

Kotelnikova, Ekaterina, Klaus M. Frahm, Dima L. Shepelyansky, and Oksana Kunduzova. "Fibrosis Protein-Protein Interactions from Google Matrix Analysis of MetaCore Network." International Journal of Molecular Sciences 23, no. 1 (2021): 67. http://dx.doi.org/10.3390/ijms23010067.

Full text

Abstract:

Protein–protein interactions is a longstanding challenge in cardiac remodeling processes and heart failure. Here, we use the MetaCore network and the Google matrix algorithms for prediction of protein–protein interactions dictating cardiac fibrosis, a primary cause of end-stage heart failure. The developed algorithms allow identification of interactions between key proteins and predict new actors orchestrating fibroblast activation linked to fibrosis in mouse and human tissues. These data hold great promise for uncovering new therapeutic targets to limit myocardial fibrosis.

APA, Harvard, Vancouver, ISO, and other styles

31

Hallen, Mark A., and Bruce R. Donald. "Protein design by provable algorithms." Communications of the ACM 62, no. 10 (2019): 76–84. http://dx.doi.org/10.1145/3338124.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

Oakley, Aaron J. "Hidden Glutathione Transferases in the Human Genome." Biomolecules 13, no. 8 (2023): 1240. http://dx.doi.org/10.3390/biom13081240.

Full text

Abstract:

With the development of accurate protein structure prediction algorithms, artificial intelligence (AI) has emerged as a powerful tool in the field of structural biology. AI-based algorithms have been used to analyze large amounts of protein sequence data including the human proteome, complementing experimental structure data found in resources such as the Protein Data Bank. The EBI AlphaFold Protein Structure Database (for example) contains over 230 million structures. In this study, these data have been analyzed to find all human proteins containing (or predicted to contain) the cytosolic glu

APA, Harvard, Vancouver, ISO, and other styles

33

Kumar, Ashish, Roheet Bhatnagar, Sumit Srivastava, and Arjun Chauhan. "Comparative Prediction of Wine Quality and Protein Synthesis Using ARSkNN." International Journal of Information Technology Project Management 11, no. 4 (2020): 31–41. http://dx.doi.org/10.4018/ijitpm.2020100103.

Full text

Abstract:

The amount of data available and information over the past few decades has grown manifold and will only increase exponentially. The ability to harvest and manipulate information from this data has become a crucial activity for effective and faster development. Multiple algorithms and approaches have been developed in order to harvest information from this data. These algorithms have different approaches and therefore result in varied outputs in terms of performance and interpretation. Due to their functionality, different algorithms perform differently on different datasets. In order to compar

APA, Harvard, Vancouver, ISO, and other styles

34

Wu, Hongjie, Haiou Li, Min Jiang, Cheng Chen, Qiang Lv, and Chuang Wu. "Identify High-Quality Protein Structural Models by EnhancedK-Means." BioMed Research International 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/7294519.

Full text

Abstract:

Background.One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases.Results.Here, we proposed two enhancedK-means clustering algorithms capable of robustly identifying high-quality protein structural models. T

APA, Harvard, Vancouver, ISO, and other styles

35

Sunny, Sharon, and P. B. Jayaraj. "A Geometric Complementarity-Based Tool for Protein–Protein Docking." Journal of Computational Biophysics and Chemistry 21, no. 01 (2021): 35–46. http://dx.doi.org/10.1142/s273741652250003x.

Full text

Abstract:

The computationally hard protein–protein complex structure prediction problem is continuously fascinating to the scientific community due to its biological impact. The field has witnessed the application of geometric algorithms, randomized algorithms, and evolutionary algorithms to name a few. These techniques improve either the searching or scoring phase. An effective searching strategy does not generate a large conformation space that perhaps demands computational power. Another determining factor is the parameter chosen for score calculation. The proposed method is an attempt to curtail the

APA, Harvard, Vancouver, ISO, and other styles

36

Lin, Guohui, Dong Xu, Zhi-Zhong Chen, Tao Jiang, Jianjun Wen, and Ying Xu. "Computational Assignment of Protein Backbone NMR Peaks by Efficient Bounding and Filtering." Journal of Bioinformatics and Computational Biology 01, no. 02 (2003): 387–409. http://dx.doi.org/10.1142/s0219720003000083.

Full text

Abstract:

NMR resonance assignment is one of the key steps in solving an NMR protein structure. The assignment process links resonance peaks to individual residues of the target protein sequence, providing the prerequisite for establishing intra- and inter-residue spatial relationships between atoms. The assignment process is tedious and time-consuming, which could take many weeks. Though there exist a number of computer programs to assist the assignment process, many NMR labs are still doing the assignments manually to ensure quality. This paper presents a new computational method based on the combinat

APA, Harvard, Vancouver, ISO, and other styles

37

Hung, Che-Lun, and Yaw-Ling Lin. "Implementation of a Parallel Protein Structure Alignment Service on Cloud." International Journal of Genomics 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/439681.

Full text

Abstract:

Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment a

APA, Harvard, Vancouver, ISO, and other styles

38

Huang, Chien-Hung, Huai-Shun Peng, and Ka-Lok Ng. "Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms." BioMed Research International 2015 (2015): 1–15. http://dx.doi.org/10.1155/2015/312047.

Full text

Abstract:

Many proteins are known to be associated with cancer diseases. It is quite often that their precise functional role in disease pathogenesis remains unclear. A strategy to gain a better understanding of the function of these proteins is to make use of a combination of different aspects of proteomics data types. In this study, we extended Aragues’s method by employing the protein-protein interaction (PPI) data, domain-domain interaction (DDI) data, weighted domain frequency score (DFS), and cancer linker degree (CLD) data to predict cancer proteins. Performances were benchmarked based on three k

APA, Harvard, Vancouver, ISO, and other styles

39

Kumar, Nilesh, and M. Shahid Mukhtar. "Ranking Plant Network Nodes Based on Their Centrality Measures." Entropy 25, no. 4 (2023): 676. http://dx.doi.org/10.3390/e25040676.

Full text

Abstract:

Biological networks are often large and complex, making it difficult to accurately identify the most important nodes. Node prioritization algorithms are used to identify the most influential nodes in a biological network by considering their relationships with other nodes. These algorithms can help us understand the functioning of the network and the role of individual nodes. We developed CentralityCosDist, an algorithm that ranks nodes based on a combination of centrality measures and seed nodes. We applied this and four other algorithms to protein–protein interactions and co-expression patte

APA, Harvard, Vancouver, ISO, and other styles

40

Westhead, D. R., V. P. Collura, M. D. Eldridge, M. A. Firth, J. Li, and C. W. Murray. "Protein fold recognition by threading: comparison of algorithms and analysis of results." "Protein Engineering, Design and Selection" 8, no. 12 (1995): 1197–204. http://dx.doi.org/10.1093/protein/8.12.1197.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

Helles, Glennie. "A comparative study of the reported performance of ab initio protein structure prediction algorithms." Journal of The Royal Society Interface 5, no. 21 (2007): 387–96. http://dx.doi.org/10.1098/rsif.2007.1278.

Full text

Abstract:

Protein structure prediction is one of the major challenges in bioinformatics today. Throughout the past five decades, many different algorithmic approaches have been attempted, and although progress has been made the problem remains unsolvable even for many small proteins. While the general objective is to predict the three-dimensional structure from primary sequence, our current knowledge and computational power are simply insufficient to solve a problem of such high complexity. Some prediction algorithms do, however, appear to perform better than others, although it is not always obvious wh

APA, Harvard, Vancouver, ISO, and other styles

42

Caliandro, Rocco, Benedetta Carrozzini, Giovanni Luca Cascarano, Giuliana Comunale, Carmelo Giacovazzo, and Annamaria Mazzone. "Protein phasing at non-atomic resolution by combining Patterson andVLDtechniques." Acta Crystallographica Section D Biological Crystallography 70, no. 7 (2014): 1994–2006. http://dx.doi.org/10.1107/s139900471401013x.

Full text

Abstract:

Phasing proteins at non-atomic resolution is still a challenge for anyab initiomethod. A variety of algorithms [Patterson deconvolution, superposition techniques, a cross-correlation function (Cmap), theVLD(vive la difference) approach, the FF function, a nonlinear iterative peak-clipping algorithm (SNIP) for defining the background of a map and thefree lunchextrapolation method] have been combined to overcome the lack of experimental information at non-atomic resolution. The method has been applied to a large number of protein diffraction data sets with resolutions varying from atomic to 2.1

APA, Harvard, Vancouver, ISO, and other styles

43

Serackis, Artūras, Dalius Matuzevičius, Dalius Navakauskas, Eldar Šabanovič, Andrius Katkevičius, and Darius Plonis. "A Robust Identification of the Protein Standard Bands in Two-Dimensional Electrophoresis Gel Images." Electrical, Control and Communication Engineering 13, no. 1 (2017): 63–68. http://dx.doi.org/10.1515/ecce-2017-0009.

Full text

Abstract:

Abstract The aim of the investigation presented in this paper was to develop a software-based assistant for the protein analysis workflow. The prior characterization of the unknown protein in two-dimensional electrophoresis gel images is performed according to the molecular weight and isoelectric point of each protein spot estimated from the gel image before further sequence analysis by mass spectrometry. The paper presents a method for automatic and robust identification of the protein standard band in a two-dimensional gel image. In addition, the method introduces the identification of the p

APA, Harvard, Vancouver, ISO, and other styles

44

Al-hussaniy, Hany Akeel. "The development of molecular docking and molecular dynamics and their application in the field of chemistry and computer simulation." Journal of medical pharmaceutical and allied sciences 12, no. 1 (2023): 5552–62. http://dx.doi.org/10.55522/jmpas.v12i1.4137.

Full text

Abstract:

With the rapid development of modern life science, computational Molecular docking has gradually become one of the core disciplines and methods of modern life science research. Computational docking studies the relationship between the structure and pharmacodynamics of biological macromolecules and the interaction between biological macromolecules and ligands. It promotes the development of protein engineering, protein design, and computer-aided drug design with powerful and various docking software in predicting the three-dimensional structure and dynamic characteristics of proteins from prot

APA, Harvard, Vancouver, ISO, and other styles

45

Lo, Victor L., Richard L. Kingston, and Rick P. Millane. "Iterative projection algorithms in protein crystallography. II. Application." Acta Crystallographica Section A Foundations and Advances 71, no. 4 (2015): 451–59. http://dx.doi.org/10.1107/s2053273315005574.

Full text

Abstract:

Iterative projection algorithms (IPAs) are a promising tool for protein crystallographic phase determination. Although related to traditional density-modification algorithms, IPAs have better convergence properties, and, as a result, can effectively overcome the phase problem given modest levels of structural redundancy. This is illustrated by applying IPAs to determine the electron densities of two protein crystals with fourfold non-crystallographic symmetry, starting with only the experimental diffraction amplitudes, a low-resolution molecular envelope and the position of the non-crystallogr

APA, Harvard, Vancouver, ISO, and other styles

46

Kim, Myeongseop, Sungjun Kim, Dabin Lee, et al. "Spatiotemporal Protein Variations Based on VIIRS-Derived Regional Protein Algorithm in the Northern East China Sea." Remote Sensing 16, no. 5 (2024): 829. http://dx.doi.org/10.3390/rs16050829.

Full text

Abstract:

Over the past two decades, the environmental characteristics of the northern East China Sea (NECS) that make it a crucial spawning ground for commercially significant species have faced substantial impacts due to climate change. Protein (PRT) within phytoplankton, serving as a nitrogen-rich food for organisms of higher trophic levels, is a sensitive indicator to environmental shifts. This study aims to develop a regional PRT algorithm to characterize spatial and temporal variations in the NECS from 2012 to 2022. Employing switching chlorophyll-a and particulate organic nitrogen algorithms, the

APA, Harvard, Vancouver, ISO, and other styles

47

Patrick, W. M., A. E. Firth, and J. M. Blackburn. "User-friendly algorithms for estimating completeness and diversity in randomized protein-encoding libraries." Protein Engineering Design and Selection 16, no. 6 (2003): 451–57. http://dx.doi.org/10.1093/protein/gzg057.

Full text

APA, Harvard, Vancouver, ISO, and other styles

48

CHANG, DARBY TIEN-HAO, JUNG-HSIN LIN, CHIH-HUNG HSIEH, and YEN-JENG OYANG. "ON THE DESIGN OF OPTIMIZATION ALGORITHMS FOR PREDICTION OF MOLECULAR INTERACTIONS." International Journal on Artificial Intelligence Tools 19, no. 03 (2010): 267–80. http://dx.doi.org/10.1142/s0218213010000182.

Full text

Abstract:

This article presents a comprehensive study on the main characteristics of a novel optimization algorithm specifically designed for simulation of protein-ligand interactions. Though design of optimization algorithms has been a research issue extensively studied by computer scientists for decades, the emerging applications in bioinformatics such as simulation of protein-ligand interactions and protein folding introduce additional challenges due to (1) the high dimensionality nature of the problem and (2) the highly rugged landscape of the energy function. As a result, optimization algorithms th

APA, Harvard, Vancouver, ISO, and other styles

49

Alshamrani, Ahmad M., Akash Saxena, Shalini Shekhawat, Hossam M. Zawbaa, and Ali Wagdy Mohamed. "Performance Evaluation of Ingenious Crow Search Optimization Algorithm for Protein Structure Prediction." Processes 11, no. 6 (2023): 1655. http://dx.doi.org/10.3390/pr11061655.

Full text

Abstract:

Protein structure prediction is one of the important aspects while dealing with critical diseases. An early prediction of protein folding helps in clinical diagnosis. In recent years, applications of metaheuristic algorithms have been substantially increased due to the fact that this problem is computationally complex and time-consuming. Metaheuristics are proven to be an adequate tool for dealing with complex problems with higher computational efficiency than conventional tools. The work presented in this paper is the development and testing of the Ingenious Crow Search Algorithm (ICSA). Firs

APA, Harvard, Vancouver, ISO, and other styles

50

Yin, Yue. "Comprehensive Analysis and Application Research of Advanced Computational Algorithms in Protein Folding Simulations." Theoretical and Natural Science 65, no. 1 (2024): 141–55. https://doi.org/10.54254/2753-8818/2024.la17930.

Full text

Abstract:

Protein engineering stands at the forefront of biotechnology, aiming to modify natural proteins or create new ones tailored to specific functional requirements. The three-dimensional structures of proteins, particularly their folding patterns, are critical in defining their biological roles. Accurate prediction and detailed examination of these protein folding structures are crucial in protein engineering. The close relationship between protein structure and function highlights the importance of understanding protein folding dynamics to successfully manipulate protein designs for intended uses

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!