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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6
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Publication Open Access Mechanistic differences of activation of Rac1(P29S) and Rac1(A159V)(American Chemical Society (ACS), 2021) Jang, Hyunbum; Nussinov, Ruth; N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Şenyüz, Simge; Keskin, Özlem; Gürsoy, Attila; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 26605; 8745Rac1 is a small GTPase that plays key roles in actin reorganization, cell motility, and cell survival/growth as well as in various cancer types and neurodegenerative diseases. Similar to other Ras superfamily GTPases, Rac1 switches between active GTP-bound and inactive GDP-bound states. Switch I and II regions open and close during GDP/GTP exchange. P29S and A159V (paralogous to K-Ras(A146)) mutations are the two most common somatic mutations of Rac1. Rac1(P2)(9S)( )is a known hotspot for melanoma, whereas Rac1(A159V) most commonly occurs in head and neck cancer. To investigate how these substitutions induce the Rac1 dynamics, we used atomistic molecular dynamics simulations on the wild-type Rac1 and two mutant systems (P29S and A159V) in the GTP bound state, and on the wild-type Rac1 and P29S mutated system in the GDP bound state. Here, we show that P29S and A159V mutations activate Rac1 with different mechanisms. In Rac1(P29S)-GTP, the substitution increases the flexibility of Switch I based on RMSF and dihedral angle calculations and leads to an open conformation. We propose that the open Switch I conformation is one of the underlying reasons for rapid GDP/GTP exchange of Rac1(P29S). On the other hand, in Rac1(A159V)-GTP, some of the contacts of the guanosine ring of GTP with Rac1 are temporarily lost, enabling the guanosine ring to move toward Switch I and subsequently close the switch. Rac1(A159V)-GTP adopts a Ras state 2 like conformation, where both switch regions are in closed conformation and Thr35 forms a hydrogen bond with the nucleotide.Publication Open Access On the rate of convergence of a classifier based on a transformer encoder(Institute of Electrical and Electronics Engineers (IEEE), 2022) Gurevych, Iryna; Kohler, Michael; Department of Computer Engineering; Şahin, Gözde Gül; Faculty Member; Department of Computer Engineering; College of Engineering; 366984Pattern recognition based on a high-dimensional predictor is considered. A classifier is defined which is based on a Transformer encoder. The rate of convergence of the misclassification probability of the classifier towards the optimal misclassification probability is analyzed. It is shown that this classifier is able to circumvent the curse of dimensionality provided the a posteriori probability satisfies a suitable hierarchical composition model. Furthermore, the difference between the Transformer classifiers theoretically analyzed in this paper and the ones used in practice today is illustrated by means of classification problems in natural language processing.Publication Open Access Adaptive reference levels in a level-crossing analog-to-digital converter(Hindawi, 2008) Guan, Karen M.; Singer, Andrew C.; Department of Computer Engineering; Kozat, Süleyman Serdar; Faculty Member; Department of Computer Engineering; College of EngineeringLevel-crossing analog-to-digital converters (LC ADCs) have been considered in the literature and have been shown to efficiently sample certain classes of signals. One important aspect of their implementation is the placement of reference levels in the converter. The levels need to be appropriately located within the input dynamic range, in order to obtain samples efficiently. In this paper, we study optimization of the performance of such an LC ADC by providing several sequential algorithms that adaptively update the ADC reference levels. The accompanying performance analysis and simulation results show that as the signal length grows, the performance of the sequential algorithms asymptotically approaches that of the best choice that could only have been chosen in hindsight within a family of possible schemes.Publication Open Access Identification of interconnected markers for T-cell acute lymphoblastic leukemia(Hindawi, 2013) Ng, Özden Hatırnaz; Department of Chemical and Biological Engineering; Department of Computer Engineering; Maiorov, Emine Güven; Keskin, Özlem; Gürsoy, Attila; PhD Student; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; N/A; 26605; 8745T-cell acute lymphoblastic leukemia (T-ALL) is a complex disease, resulting from proliferation of differentially arrested immature T cells. The molecular mechanisms and the genes involved in the generation of T-ALL remain largely undefined. In this study, we propose a set of genes to differentiate individuals with T-ALL from the nonleukemia/healthy ones and genes that are not differential themselves but interconnected with highly differentially expressed ones. We provide new suggestions for pathways involved in the cause of T-ALL and show that network-based classification techniques produce fewer genes with more meaningful and successful results than expression-based approaches. We have identified 19 significant subnetworks, containing 102 genes. The classification/prediction accuracies of subnetworks are considerably high, as high as 98%. Subnetworks contain 6 nondifferentially expressed genes, which could potentially participate in pathogenesis of T-ALL. Although these genes are not differential, they may serve as biomarkers if their loss/gain of function contributes to generation of T-ALL via SNPs. We conclude that transcription factors, zinc-ion-binding proteins, and tyrosine kinases are the important protein families to trigger T-ALL. These potential disease-causing genes in our subnetworks may serve as biomarkers, alternative to the traditional ones used for the diagnosis of T-ALL, and help understand the pathogenesis of the disease.Publication Open Access Cryptochrome deletion in p53 mutant mice enhances apoptotic and anti-tumorigenic responses to UV damage at the transcriptome level(Springer, 2019) Korkmaz, Tuba; Özturk, Nuri; Department of Chemical and Biological Engineering; Department of Molecular Biology and Genetics; Department of Computer Engineering; N/A; Kavaklı, İbrahim Halil; Keskin, Özlem; Cavga, Ayşe Derya; Gürsoy, Attila; Tardu, Mehmet; Faculty Member; Faculty Member; PhD Student; Department of Chemical and Biological Engineering; Department of Molecular Biology and Genetics; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; 40319; 26605; N/A; 8745; N/APrevious studies have demonstrated that deletion of cryptochrome (Cry) genes protects p53(-/-) mutant mice from the early onset of cancer and extends their median life-span by about 1.5-fold. Subsequent in vitro studies had revealed that deletion of Crys enhances apoptosis in response to UV damage through activation of p73 and inactivation of GSK3 beta. However, it was not known at the transcriptome-wide level how deletion of Crys delays the onset of cancer in p53(-/-) mutant mice. In this study, the RNA-seq approach was taken to uncover the differentially expressed genes (DEGs) and pathways following UV-induced DNA damage in p53(-/-) and p53(-/-)Cry1(-/-)Cry2(-/-) mouse skin fibroblasts. Gene set enrichment analysis with the DEGs demonstrated enrichment in immune surveillance-associated genes regulated by IFN-gamma and genes involved in TNF alpha signaling via NF-kappa B. Furthermore, protein network analysis enabled identification of DEGs p21, Sirt1, and Jun as key players, along with their interacting partners. It was also observed that the DEGs contained a high ratio of non-coding transcripts. Collectively, the present study suggests new genes in NF-kappa B regulation and IFN-gamma response, as well as non-coding RNAs, may contribute to delaying the onset of cancer in p53(-/-)Cry1(-/-)Cry2(-/-) mice and increasing the life-span of these animals compared to p53(-/-) mice.Publication Open Access Deep stroke-based sketched symbol reconstruction and segmentation(Institute of Electrical and Electronics Engineers (IEEE), 2020) Department of Computer Engineering; N/A; Sezgin, Tevfik Metin; Kaiyrbekov, Kurmanbek; Faculty Member; Department of Computer Engineering; College of Engineering; Graduate School of Sciences and Engineering; 18632; N/AHand-drawn objects usually consist of multiple semantically meaningful parts. In this article, we propose a neural network model that segments sketched symbols into stroke-level components. Our segmentation framework has two main elements: a fixed feature extractor and a multilayer perceptron (MLP) network that identifies a component based on the feature. As the feature extractor we utilize an encoder of a stroke-rnn, which is our newly proposed generative variational auto-encoder (VAE) model that reconstructs symbols on a stroke-by-stroke basis. Experiments show that a single encoder could be reused for segmenting multiple categories of sketched symbols with negligible effects on segmentation accuracies. Our segmentation scores surpass existing methodologies on an available small state-of-the-art dataset. Moreover, extensive evaluations on our newly annotated big dataset demonstrate that our framework obtains significantly better accuracies as compared to baseline models. We release the dataset to the community.Publication Open Access Density-based 3D shape descriptors(Springer, 2007) Akgül, Ceyhun Burak; Sankur, Bülent; Schmitt, Francis; Department of Computer Engineering; Yemez, Yücel; Faculty Member; Department of Computer Engineering; College of EngineeringWe propose a novel probabilistic framework for the extraction of density-based 3D shape descriptors using kernel density estimation. Our descriptors are derived from the probability density functions (pdf) of local surface features characterizing the 3D object geometry. Assuming that the shape of the 3D object is represented as a mesh consisting of triangles with arbitrary size and shape, we provide efficient means to approximate the moments of geometric features on a triangle basis. Our framework produces a number of 3D shape descriptors that prove to be quite discriminative in retrieval applications. We test our descriptors and compare them with several other histogram-based methods on two 3D model databases, Princeton Shape Benchmark and Sculpteur, which are fundamentally different in semantic content and mesh quality. Experimental results show that our methodology not only improves the performance of existing descriptors, but also provides a rigorous framework to advance and to test new ones.Publication Open Access Parser evaluation using textual entailments(Springer, 2013) Rimell, Laura; Department of Computer Engineering; Yüret, Deniz; Han, Aydın; Faculty Member; Master Student; Department of Computer Engineering; College of Engineering; Graduate School of Sciences and Engineering; 179996; N/AParser Evaluation using Textual Entailments (PETE) is a shared task in the SemEval-2010 Evaluation Exercises on Semantic Evaluation. The task involves recognizing textual entailments based on syntactic information alone. PETE introduces a new parser evaluation scheme that is formalism independent, less prone to annotation error, and focused on semantically relevant distinctions. This paper describes the PETE task, gives an error analysis of the top-performing Cambridge system, and introduces a standard entailment module that can be used with any parser that outputs Stanford typed dependencies.Publication Open Access Normal mode analysis of KRas4B reveals partner specific dynamics(American Chemical Society (ACS), 2021) Jang, Hyunbum; Nussinov, Ruth; Department of Molecular Biology and Genetics; Department of Chemical and Biological Engineering; Department of Computer Engineering; Tunçbağ, Nurcan; Gürsoy, Attila; Keskin, Özlem; Eren, Meryem; Faculty Member; Faculty Member; Department of Molecular Biology and Genetics; Department of Chemical and Biological Engineering; Department of Computer Engineering; School of Medicine; College of Engineering; Graduate School of Sciences and Engineering; 245513; 8745; 26605; N/ARas GTPase interacts with its regulators and downstream effectors for its critical function in cellular signaling. Targeting the disrupted mechanisms in Ras-related human cancers requires understanding the distinct dynamics of these protein-protein interactions. We performed normal mode analysis (NMA) of KRas4B in wild-type or mutant monomeric and neurofibromin-1 (NF1), Son of Sevenless 1 (SOS1) or Raf-1 bound dimeric conformational states to reveal partner-specific dynamics of the protein. Gaussian network model (GNM) analysis showed that the known KRas4B lobes further partition into subdomains upon binding to its partners. Furthermore, KRas4B interactions with different partners suppress the flexibility in not only their binding sites but also distant residues in the allosteric lobe in a partner-specific way. The conformational changes can be driven by intrinsic residue fluctuations of the open state KRas4B-GDP, as we illustrated with anisotropic network model (ANM) analysis. The allosteric paths connecting the nucleotide binding residues to the allosteric site at alpha 3-L7 portray differences in the inactive and active states. These findings help in understanding the partner-specific KRas4B dynamics, which could be utilized for therapeutic targeting.Publication Open Access Mode coupling points to functionally important residues in myosin II(Wiley, 2014) Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Physics; Varol, Onur; Yüret, Deniz; Erman, Burak; Kabakçıoğlu, Alkan; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Physics; Graduate School of Sciences and Engineering; College of Engineering; College of Sciences; N/A; 179996; 179997; 49854Relevance of mode coupling to energy/information transfer during protein function, particularly in the context of allosteric interactions is widely accepted. However, existing evidence in favor of this hypothesis comes essentially from model systems. We here report a novel formal analysis of the near-native dynamics of myosin II, which allows us to explore the impact of the interaction between possibly non-Gaussian vibrational modes on fluctutational dynamics. We show that an information-theoretic measure based on mode coupling alone yields a ranking of residues with a statistically significant bias favoring the functionally critical locations identified by experiments on myosin II.