Search for: protein-analysis
Whole-genome analysis of de novo somatic point mutations reveals novel mutational biomarkers in pancreatic cancer, Article Cancers ; Volume 13, Issue 17 , 2021 ; 20726694 (ISSN) ; Mohseni, A ; Dashti, H ; Beheshti, A ; Dehzangi, A ; Rabiee, H. R ; Alinejad Rokny, H ; Sharif University of Technology
It is now known that at least 10% of samples with pancreatic cancers (PC) contain a causative mutation in the known susceptibility genes, suggesting the importance of identifying cancer-associated genes that carry the causative mutations in high-risk individuals for early detection of PC. In this study, we develop a statistical pipeline using a new concept, called gene-motif, that utilizes both mutated genes and mutational processes to identify 4211 3-nucleotide PC-associated gene-motifs within 203 significantly mutated genes in PC. Using these gene-motifs as distinguishable features for pancreatic cancer subtyping results in identifying five PC subtypes with distinguishable phenotypes and...
Substrate oscillations boost recombinant protein release from Escherichia coli, Article Bioprocess and Biosystems Engineering ; Volume 37, Issue 5 , May , 2014 , Pages 881-890 ; ISSN: 16157591 ; Herwig, C ; Sharif University of Technology
Intracellular production of recombinant proteins in prokaryotes necessitates subsequent disruption of cells for protein recovery. Since the cell disruption and subsequent purification steps largely contribute to the total production cost, scalable tools for protein release into the extracellular space is of utmost importance. Although there are several ways for enhancing protein release, changing culture conditions is rather a simple and scalable approach compared to, for example, molecular cell design. This contribution aimed at quantitatively studying process technological means to boost protein release of a periplasmatic recombinant protein (alkaline phosphatase) from E. coli....
StrongestPath: a Cytoscape application for protein-protein interaction analysis, Article BMC bioinformatics ; Volume 22, Issue 1 , 2021 , Pages 352- ; 14712105 (ISSN) ; Khodabandeh, M ; Sharifi Zarchi, A ; Nadafian, A ; Mahmoudi, A ; Sharif University of Technology
NLM (Medline) 2021
BACKGROUND: StrongestPath is a Cytoscape 3 application that enables the analysis of interactions between two proteins or groups of proteins in a collection of protein-protein interaction (PPI) network or signaling network databases. When there are different levels of confidence over the interactions, the application is able to process them and identify the cascade of interactions with the highest total confidence score. Given a set of proteins, StrongestPath can extract a set of possible interactions between the input proteins, and expand the network by adding new proteins that have the most interactions with highest total confidence to the current network of proteins. The application can...
NETAL: A new graph-based method for global alignment of protein-protein interaction networks, Article Bioinformatics ; Volume 29, Issue 13 , 2013 , Pages 1654-1662 ; 13674803 (ISSN) ; Khadem, A ; Hashemifar, S ; Arab, S. S ; Sharif University of Technology
Motivation: The interactions among proteins and the resulting networks of such interactions have a central role in cell biology. Aligning these networks gives us important information, such as conserved complexes and evolutionary relationships. Although there have been several publications on the global alignment of protein networks; however, none of proposed methods are able to produce a highly conserved and meaningful alignment. Moreover, time complexity of current algorithms makes them impossible to use for multiple alignment of several large networks together.Results: We present a novel algorithm for the global alignment of protein-protein interaction networks. It uses a greedy method,...
Molecularly imprinted polydopamine nano-layer on the pore surface of porous particles for protein capture in HPLC column, Article Journal of Colloid and Interface Science ; Volume 404 , 2013 , Pages 117-126 ; 00219797 (ISSN) ; Shojaei, A ; Abdekhodaie, M. J ; Sellergren, B ; Sharif University of Technology
Bio-inspired Human Serum Albumin (HSA) imprinted polydopamine nano-layer was produced through oxidative polymerization of dopamine on the pore surface of HSA modified porous silica particles. The coating thickness was controlled by the reaction time and thereby varied within 0-12. nm. The samples were characterized by elemental analysis, FT-IR, DSC, SEM, TEM, TGA, physisorption and thermoporometry. The characterization confirmed the success of evolution and deposition of polydopamine layer on the silica pore surface. Batch rebinding experiment showed that the molecularly imprinted polymer (MIP) with 8.7. nm coating thickness, in comparison with the thinner and thicker coatings, displays the...
Mechanical differences between ATP and ADP actin states: A molecular dynamics study, Article Journal of Theoretical Biology ; Volume 448 , 2018 , Pages 94-103 ; 00225193 (ISSN) ; Shamloo, A ; Sharif University of Technology
Academic Press 2018
This paper aims to give a comprehensive atomistic modeling of the nanomechanical behavior of actin monomer. Actin is a ubiquitous and essential component of cytoskeleton which forms many different cellular structures. Despite for several years great effort has been devoted to the investigation of mechanical properties of the actin filament, studies on the nanomechanical behavior of actin monomer are still lacking. These scales are, however, important for a complete understanding of the role of actin as an important component in the cytoskeleton structure. Based on the accuracy of atomistic modeling methods such as molecular dynamics simulations, steered molecular dynamics method is performed...
Inferring causal molecular networks: Empirical assessment through a community-based effort, Article Nature Methods ; Volume 13, Issue 4 , 2016 , Pages 310-322 ; 15487091 (ISSN) ; Heiser, L.M ; Cokelaer, T ; Linger, M ; Nesser, N. K ; Carlin, D. E ; Zhang, Y ; Sokolov, A ; Paull, E. O ; Wong, C. K ; Graim, K ; Bivol, A ; Wang, H ; Zhu, F ; Afsari, B ; Danilova, L. V ; Favorov, A. V ; Lee, W. S ; Taylor, D ; Hu, C. W ; Long, B. L ; Noren, D. P ; Bisberg, A. J ; Mills, G. B ; Gray, J. W ; Kellen, M ; Norman, T ; Friend, S ; Qutub, A. A ; Fertig, E. J ; Guan, Y ; Song, M ; Stuart, J. M ; Spellman, P. T ; Koeppl, H ; Stolovitzky, G ; Saez Rodriguez, J ; Mukherjee, S ; Afsari, B ; Al-Ouran, R ; Anton, B ; Arodz, T ; Askari Sichani, O ; Bagheri, N ; Berlow, N ; Bisberg, A. J ; Bivol, A ; Bohler, A ; Bonet, J ; Bonneau, R ; Budak, G ; Bunescu, R ; Caglar, M ; Cai, B ; Cai, C ; Carlin, D. E ; Carlon, A ; Chen, L ; Ciaccio, M. F ; Cokelaer, T ; Cooper, G ; Coort, S ; Creighton, C. J ; Daneshmand, S. M. H ; De La Fuente, A ; Di Camillo, B ; Danilova, L. V ; Dutta-Moscato, J ; Emmett, K ; Evelo, C ; Fassia, M. K. H ; Favorov, A. V ; Fertig, E. J ; Finkle, J. D ; Finotello, F ; Friend, S ; Gao, X ; Gao, J ; Garcia Garcia, J ; Ghosh, S ; Giaretta, A ; Graim, K ; Gray, J. W ; Großeholz, R ; Guan, Y ; Guinney, J ; Hafemeister, C ; Hahn, O ; Haider, S ; Hase, T ; Heiser, L. M ; Hill, S. M ; Hodgson, J ; Hoff, B ; Hsu, C. H ; Hu, C. W ; Hu, Y ; Huang, X ; Jalili, M ; Jiang, X ; Kacprowski, T ; Kaderali, L ; Kang, M ; Kannan, V ; Kellen, M ; Kikuchi, K ; Kim, D. C ; Kitano, H ; Knapp, B ; Komatsoulis, G ; Koeppl, H ; Krämer, A ; Kursa, M. B ; Kutmon, M ; Lee, W. S ; Li, Y ; Liang, X ; Liu, Z ; Liu, Y ; Long, B. L ; Lu, S ; Lu, X ; Manfrini, M ; Matos, M. R. A ; Meerzaman, D ; Mills, G. B ; Min, W ; Mukherjee, S ; Müller, C. L ; Neapolitan, R. E ; Nesser, N. K ; Noren, D. P ; Norman, T ; Oliva, B ; Opiyo, S. O ; Pal, R ; Palinkas, A ; Paull, E. O ; Planas Iglesias, J ; Poglayen, D ; Qutub, A. A ; Saez Rodriguez, J ; Sambo, F ; Sanavia, T ; Sharifi-Zarchi, A ; Slawek, J ; Sokolov, A ; Song, M ; Spellman, P. T ; Streck, A ; Stolovitzky, G ; Strunz, S ; Stuart, J. M ; Taylor, D ; Tegnér, J ; Thobe, K ; Toffolo, G. M ; Trifoglio, E ; Unger, M ; Wan, Q ; Wang, H ; Welch, L ; Wong, C. K ; Wu, J. J ; Xue, A. Y ; Yamanaka, R ; Yan, C ; Zairis, S ; Zengerling, M ; Zenil, H ; Zhang, S ; Zhang, Y ; Zhu, F ; Zi, Z ; Sharif University of Technology
Nature Publishing Group 2016
It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was...
Glypican-1 overexpression in different types of breast cancers, Article OncoTargets and Therapy ; Volume 14 , 2021 , Pages 4309-4318 ; 11786930 (ISSN) ; Al Saraireh, Y. M ; Youssef, A. M. M ; Al Sarayra, Y. M ; Alrawashdeh, H. M ; Sharif University of Technology
Dove Medical Press Ltd 2021
Purpose: Treatment of metastatic breast cancer patients is challenging and remains a major underlying cause of female mortality. Understanding molecular alterations in tumor development is critical to identify novel biomarkers and targets for cancer diagnosis and therapy. One of the aberrant cancer expressions gaining recent research interest is glypican-1. Several studies reported strong glypican-1 expression in various types of human cancers. However, none of these investigated glypican-1 expression in a large cohort of breast cancer histopathological subtypes. Patients and Methods: Immunohistochemistry was used to assess glypican-1 expression in 220 breast cancer patients and its relation...
A tale of two symmetrical tails: Structural and functional characteristics of palindromes in proteins, Article BMC Bioinformatics ; Volume 9 , 2008 ; 14712105 (ISSN) ; Kargar, M ; Katanforoush, A ; Arab, S ; Sadeghi, M ; Pezeshk, H ; Eslahchi, C ; Marashi, S. A ; Sharif University of Technology
Background: It has been previously shown that palindromic sequences are frequently observed in proteins. However, our knowledge about their evolutionary origin and their possible importance is incomplete. Results: In this work, we tried to revisit this relatively neglected phenomenon. Several questions are addressed in this work. (1) It is known that there is a large chance of finding a palindrome in low complexity sequences (i.e. sequences with extreme amino acid usage bias). What is the role of sequence complexity in the evolution of palindromic sequences in proteins? (2) Do palindromes coincide with conserved protein sequences? If yes, what are the functions of these conserved segments?...
AntAngioCOOL: computational detection of anti-angiogenic peptides, Article Journal of Translational Medicine ; Volume 17, Issue 1 , 2019 ; 14795876 (ISSN) ; Khorsand, B ; Yousefi, A. A ; Kargar, M. J ; Shirali Hossein Zade, R ; Mahdevar, G ; Sharif University of Technology
BioMed Central Ltd 2019
Background: Angiogenesis inhibition research is a cutting edge area in angiogenesis-dependent disease therapy, especially in cancer therapy. Recently, studies on anti-angiogenic peptides have provided promising results in the field of cancer treatment. Methods: A non-redundant dataset of 135 anti-angiogenic peptides (positive instances) and 135 non anti-angiogenic peptides (negative instances) was used in this study. Also, 20% of each class were selected to construct an independent test dataset (see Additional files 1, 2). We proposed an effective machine learning based R package (AntAngioCOOL) to predict anti-angiogenic peptides. We have examined more than 200 different classifiers to build...
A novel pattern matching algorithm for genomic patterns related to protein motifs, Article Journal of Bioinformatics and Computational Biology ; Volume 18, Issue 1 , 2020 ; Goliaei, S ; Goliaei, B ; Sharif University of Technology
World Scientific Publishing Co. Pte Ltd 2020
Patterns on proteins and genomic sequences are vastly analyzed, extracted and collected in databases. Although protein patterns originate from genomic coding regions, very few works have directly or indirectly dealt with coding region patterns induced from protein patterns. Results: In this paper, we have defined a new genomic pattern structure suitable for representing induced patterns from proteins. The provided pattern structure, which is called "Consecutive Positions Scoring Matrix (CPSSM)", is a replacement for protein patterns and profiles in the genomic context. CPSSMs can be identified, discovered, and searched in genomes. Then, we have presented a novel pattern matching algorithm...