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394 results on '"Jahandideh, Samad"'

17. Numerous proteins with unique characteristics are degraded by the 26S proteasome following monoubiquitination

Author

Braten, Ori, Livneh, Ido, Ziv, Tamar, Admon, Arie, Kehat, Izhak, Caspi, Lilac H, Gonen, Hedva, Bercovich, Beatrice, Godzik, Adam, Jahandideh, Samad, Jaroszewski, Lukasz, Sommer, Thomas, Kwon, Yong Tae, Guharoy, Mainak, Tompa, Peter, and Ciechanover, Aaron

Subjects
1.1 Normal biological development and functioning, Underpinning research, Generic health relevance, Humans, MCF-7 Cells, Proteasome Endopeptidase Complex, Proteins, Proteomics, Ubiquitination, monoubiquitination, 26S proteasome, protein degradation, ubiquitin replacement
Abstract

The "canonical" proteasomal degradation signal is a substrate-anchored polyubiquitin chain. However, a handful of proteins were shown to be targeted following monoubiquitination. In this study, we established-in both human and yeast cells-a systematic approach for the identification of monoubiquitination-dependent proteasomal substrates. The cellular wild-type polymerizable ubiquitin was replaced with ubiquitin that cannot form chains. Using proteomic analysis, we screened for substrates that are nevertheless degraded under these conditions compared with those that are stabilized, and therefore require polyubiquitination for their degradation. For randomly sampled representative substrates, we confirmed that their cellular stability is in agreement with our screening prediction. Importantly, the two groups display unique features: monoubiquitinated substrates are smaller than the polyubiquitinated ones, are enriched in specific pathways, and, in humans, are structurally less disordered. We suggest that monoubiquitination-dependent degradation is more widespread than assumed previously, and plays key roles in various cellular processes.

Published
2016

19. PROPER: Performance visualization for optimizing and comparing ranking classifiers in MATLAB

Author

Jahandideh, Samad, Sharifi, Fatemeh, Jaroszewski, Lukasz, and Godzik, Adam

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Networking and Information Technology R&D (NITRD), Bioengineering, Predictive modeling, Scoring classifier, Big data, Structural genomics, Biochemistry and Cell Biology, Computer Software, Bioinformatics, Bioinformatics and computational biology
Abstract

BackgroundOne of the recent challenges of computational biology is development of new algorithms, tools and software to facilitate predictive modeling of big data generated by high-throughput technologies in biomedical research.ResultsTo meet these demands we developed PROPER - a package for visual evaluation of ranking classifiers for biological big data mining studies in the MATLAB environment.ConclusionPROPER is an efficient tool for optimization and comparison of ranking classifiers, providing over 20 different two- and three-dimensional performance curves.

Published
2015

20. Improving the chances of successful protein structure determination with a random forest classifier

Author

Jahandideh, Samad, Jaroszewski, Lukasz, and Godzik, Adam

Subjects
Biotechnology, Algorithms, Amino Acids, Artificial Intelligence, Computer Simulation, Crystallization, Crystallography, X-Ray, Hydrophobic and Hydrophilic Interactions, Neural Networks, Computer, Predictive Value of Tests, Proteins, Random Allocation, Support Vector Machine, XtalPred, machine-learning methods, structural genomics, target selection, Physical Sciences, Chemical Sciences, Biological Sciences, Biophysics
Abstract

Obtaining diffraction quality crystals remains one of the major bottlenecks in structural biology. The ability to predict the chances of crystallization from the amino-acid sequence of the protein can, at least partly, address this problem by allowing a crystallographer to select homologs that are more likely to succeed and/or to modify the sequence of the target to avoid features that are detrimental to successful crystallization. In 2007, the now widely used XtalPred algorithm [Slabinski et al. (2007), Protein Sci. 16, 2472-2482] was developed. XtalPred classifies proteins into five `crystallization classes' based on a simple statistical analysis of the physicochemical features of a protein. Here, towards the same goal, advanced machine-learning methods are applied and, in addition, the predictive potential of additional protein features such as predicted surface ruggedness, hydrophobicity, side-chain entropy of surface residues and amino-acid composition of the predicted protein surface are tested. The new XtalPred-RF (random forest) achieves significant improvement of the prediction of crystallization success over the original XtalPred. To illustrate this, XtalPred-RF was tested by revisiting target selection from 271 Pfam families targeted by the Joint Center for Structural Genomics (JCSG) in PSI-2, and it was estimated that the number of targets entered into the protein-production and crystallization pipeline could have been reduced by 30% without lowering the number of families for which the first structures were solved. The prediction improvement depends on the subset of targets used as a testing set and reaches 100% (i.e. twofold) for the top class of predicted targets.

Published
2014

26. Live birth per embryo transfer with next generation sequencing preimplantation genetic testing: an analysis of 26,107 cycles.

Author

Sarkar, Papri, New, Erika P., Sprague, Rachel G., Stillman, Robert, Widra, Eric, Jahandideh, Samad, Devine, Kate, and Imudia, Anthony N.

Subjects
NUCLEOTIDE sequencing, EMBRYO transfer, GENETIC testing, OVARIAN reserve, FERTILIZATION in vitro, BIRTH rate
Abstract

The technique and platform used for preimplantation genetic testing for aneuploidy (PGT-A) have undergone significant changes over time. The contemporary technique utilizes trophectoderm biopsy followed by next-generation sequencing (NGS). The goal of this study was to explore the role of PGT-A using NGS technique exclusively in contemporary in vitro fertilization (IVF) practice. For this, we performed a retrospective analysis of a large dataset collected from the Shady Grove Fertility (SGF) multicentre practice. All autologous IVF cycles which were followed by at least one single embryo transfer (ET) (fresh and/or frozen) between January 2017 to July 2020, were included. Our study group included patients who had PGT-A and the control group included patients who did not proceed with PGT-A. The primary outcome was the live birth rate (LBR) per transfer. All age-adjusted LBR was higher in the PGT-A group than the non-PGT-A group (48.9% vs. 42.7%, p < 0.001), except in women <35 years old among single embryo frozen ETs. Similarly, LBR in the PGT-A group was higher in all ages except in women <35 years old (48.7% vs. 41.7%, p < 0.001) when all single embryos fresh and frozen ETs were included. In patients of decreased ovarian reserve, transfer of euploid embryo was associated with higher LBR (46.7% vs. 26.7%, p < 0.001) whereas miscarriages were lower in patients with unexplained infertility (9.3% vs. 11.3%, p = 0.007 and endometriosis (8.9% vs. 11.6%, p < 0.001) following euploid embryo transfer. To conclude, the transfer of euploid embryos tested via NGS PGT-A was associated with improved LBR per transfer in women ≥35 years old. [ABSTRACT FROM AUTHOR]

Published
2023
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27. Reproductive genetics laboratory may impact euploid blastocyst and live birth rates: a comparison of 4 national laboratories' PGT-A results from vitrified donor oocytes

Author

Bardos, Jonah, primary, Kwal, Jaclyn, additional, Caswell, Wayne, additional, Jahandideh, Samad, additional, Stratton, Melissa, additional, Tucker, Michael, additional, DeCherney, Alan, additional, Devine, Kate, additional, Hill, Micah, additional, and O’Brien, Jeanne E., additional

Published
2023
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42. A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection

Author

Fourati, Slim, Talla, Aarthi, Mahmoudian, Mehrad, Burkhart, Joshua G., Klén, Riku, Henao, Ricardo, Yu, Thomas, Aydın, Zafer, Yeung, Ka Yee, Ahsen, Mehmet Eren, Almugbel, Reem, Jahandideh, Samad, Liang, Xiao, Nordling, Torbjörn E. M., Shiga, Motoki, Stanescu, Ana, Vogel, Robert, The Respiratory Viral DREAM Challenge Consortium, Pandey, Gaurav, Chiu, Christopher, McClain, Micah T., Woods, Christopher W., Ginsburg, Geoffrey S., Elo, Laura L., Tsalik, Ephraim L., Mangravite, Lara M., and Sieberts, Solveig K.

Published
2018
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