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Publication Metadata only A communication theoretical modeling of axonal propagation in hippocampal pyramidal neurons(IEEE-Inst Electrical Electronics Engineers Inc, 2017) N/A; N/A; Department of Electrical and Electronics Engineering; Ramezani, Hamideh; Akan, Özgür Barış; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 6647Understandingthe fundamentals of communication among neurons, known as neuro-spike communication, leads to reach bio-inspired nanoscale communication paradigms. In this paper, we focus on a part of neuro-spike communication, known as axonal transmission, and propose a realistic model for it. The shape of the spike during axonal transmission varies according to previously applied stimulations to the neuron, and these variations affect the amount of information communicated between neurons. Hence, to reach an accurate model for neuro-spike communication, the memory of axon and its effect on the axonal transmission should be considered, which are not studied in the existing literature. In this paper, we extract the important factors on the memory of axon and define memory states based on these factors. We also describe the transition among these states and the properties of axonal transmission in each of them. Finally, we demonstrate that the proposed model can follow changes in the axonal functionality properly by simulating the proposed model and reporting the root mean square error between simulation results and experimental data.Publication Metadata only A fast algorithm for analysis of molecular communication in artificial synapse(IEEE-Inst Electrical Electronics Engineers Inc, 2017) N/A; Department of Electrical and Electronics Engineering; Bilgin, Bilgesu Arif; Akan, Özgür Barış; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 6647In this paper, we analyze molecular communications (MCs) in a proposed artificial synapse (AS), whose main difference from biological synapses (BSs) is that it is closed, i.e., transmitter molecules cannot diffuse out from AS. Such a setup has both advantages and disadvantages. Besides higher structural stability, being closed, AS never runs out of transmitters. Thus, MC in AS is disconnected from outer environment, which is very desirable for possible intra-body applications. On the other hand, clearance of transmitters from AS has to be achieved by transporter molecules on the presynaptic membrane of AS. Except from these differences, rest of AS content is taken to be similar to that of a glutamatergic BS. Furthermore, in place of commonly used Monte Carlo-based random walk experiments, we derive a deterministic algorithm that attacks for expected values of desired parameters such as evolution of receptor states. To assess validity of our algorithm, we compare its results with average results of an ensemble of Monte Carlo experiments, which shows near exact match. Moreover, our approach requires significantly less amount of computation compared with Monte Carlo approach, making it useful for parameter space exploration necessary for optimization in design of possible MC devices, including but not limited to AS. Results of our algorithm are presented in case of single quantal release only, and they support that MC in closed AS with elevated uptake has similar properties to that in BS. In particular, similar to glutamatergic BSs, the quantal size and the density of receptors are found to be main sources of synaptic plasticity. On the other hand, the proposed model of AS is found to have slower decaying transients of receptor states than BSs, especially desensitized ones, which is due to prolonged clearance of transmitters from AS.Publication Metadata only A multitask multiple kernel learning formulation for discriminating early- and late-stage cancers(Oxford University Press (OUP), 2020) N/A; N/A; Department of Industrial Engineering; Rahimi, Arezou; Gönen, Mehmet; PhD Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 237468Motivation: Genomic information is increasingly being used in diagnosis, prognosis and treatment of cancer. The severity of the disease is usually measured by the tumor stage. Therefore, identifying pathways playing an important role in progression of the disease stage is of great interest. Given that there are similarities in the underlying mechanisms of different cancers, in addition to the considerable correlation in the genomic data, there is a need for machine learning methods that can take these aspects of genomic data into account. Furthermore, using machine learning for studying multiple cancer cohorts together with a collection of molecular pathways creates an opportunity for knowledge extraction. Results: We studied the problem of discriminating early- and late-stage tumors of several cancers using genomic information while enforcing interpretability on the solutions. To this end, we developed a multitask multiple kernel learning (MTMKL) method with a co-clustering step based on a cutting-plane algorithm to identify the relationships between the input tasks and kernels. We tested our algorithm on 15 cancer cohorts and observed that, in most cases, MTMKL outperforms other algorithms (including random forests, support vector machine and single-task multiple kernel learning) in terms of predictive power. Using the aggregate results from multiple replications, we also derived similarity matrices between cancer cohorts, which are, in many cases, in agreement with available relationships reported in the relevant literature.Publication Metadata only A proteomic analysis of mitochondrial complex iii inhibition in SH-SY5Y human neuroblastoma cell line(Bentham Science, 2019) Acioglu, Cigdem; Tuzuner, Mete Bora; Serhatli, Muge; Sahin, Betul; Akgun, Emel; Adiguzel, Zelal; Gurel, Busra; Baykal, Ahmet Tarik; Ayhan, Ceyda Açılan; Faculty Member; School of Medicine; 219658Background and Objective: Antimycin A (AntA) is a potent Electron Transport System (ETS) inhibitor exerting its effect through inhibiting the transfer of the electrons by binding to the quinone reduction site of the cytochrome bcl complex (Complex III), which is known to be impaired in Huntington's Disease (HD). The current studies were undertaken to investigate the effect of complex III inhibition in the SH-SY5Y cell line to delineate the molecular and cellular processes, which may play a role in the pathogenesis of HD. Method: We treated SH-SY5Y neuroblastoma cells with AntA in order to establish an in vitro mitochondrial dysfunction model for HD. Differential proteome analysis was performed by the nLC-MS/MS system. Protein expression was assessed by western blot analysis. Results: Thirty five differentially expressed proteins as compared to the vehicle-treated controls were detected. Functional pathway analysis indicated that proteins involved in ubiquitin-proteasomal pathway were up-regulated in AntA-treated SH-SY5Y neuroblastoma cells and the ubiquitinated protein accumulation was confirmed by immunoblotting. We found that Prothymosin alpha (ProT alpha) was down-regulated. Furthermore, we demonstrated that nuclear factor erythroid 2-related factor 2 (Nrf2) protein expression was co-regulated with ProT alpha expression, hence knockdown of ProT alpha in SH-SY5Y cells decreased Nrf2 protein level. Conclusion: Our findings suggest that complex III impairment might downregulate ubiquitin-proteasome function and NRF2/Keapl antioxidant response. In addition, it is likely that downregulation of Nrf2 is due to the decreased expression of ProT alpha in AntA-treated SH-SY5Y cells. Our results could advance the understanding of mechanisms involved in neurodegenerative diseases.Publication Metadata only A survey of available tools and web servers for analysis of protein-protein interactions and interfaces(Oxford University Press (OUP), 2009) Nussinov, Ruth; Department of Chemical and Biological Engineering; Department of Computer Engineering; N/A; Department of Chemical and Biological Engineering; Keskin, Özlem; Gürsoy, Attila; Makinacı, Gözde Kar; Tunçbağ, Nurcan; Faculty Member; Faculty Member; PhD Student; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; 26605; 8745; N/A; 245513The unanimous agreement that cellular processes are (largely) governed by interactions between proteins has led to enormous community efforts culminating in overwhelming information relating to these proteins; to the regulation of their interactions, to the way in which they interact and to the function which is determined by these interactions. These data have been organized in databases and servers. However, to make these really useful, it is essential not only to be aware of these, but in particular to have a working knowledge of which tools to use for a given problem; what are the tool advantages and drawbacks; and no less important how to combine these for a particular goal since usually it is not one tool, but some combination of tool-modules that is needed. This is the goal of this review.Publication Metadata only An approach to monitoring home-cage behavior in mice that facilitates data sharing(Nature Portfolio, 2018) Balzani, Edoardo; Falappa, Matteo; Tucci, Valter; Department of Psychology; Balcı, Fuat; Faculty Member; Department of Psychology; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); College of Social Sciences and Humanities; 51269Genetically modified mice are used as models for a variety of human behavioral conditions. However, behavioral phenotyping can be a major bottleneck in mouse genetics because many of the classic protocols are too long and/or are vulnerable to unaccountable sources of variance, leading to inconsistent results between centers. We developed a home-cage approach using a Chora feeder that is controlled by-and sends data to-software. In this approach, mice are tested in the standard cages in which they are held for husbandry, which removes confounding variables such as the stress induced by out-of-cage testing. This system increases the throughput of data gathering from individual animals and facilitates data mining by offering new opportunities for multimodal data comparisons. In this protocol, we use a simple work-for-food testing strategy as an example application, but the approach can be adapted for other experiments looking at, e.g., attention, decision-making or memory. The spontaneous behavioral activity of mice in performing the behavioral task can be monitored 24 h a day for several days, providing an integrated assessment of the circadian profiles of different behaviors. We developed a Python-based open-source analytical platform (Phenopy) that is accessible to scientists with no programming background and can be used to design and control such experiments, as well as to collect and share data. This approach is suitable for large-scale studies involving multiple laboratories.Publication Metadata only Analysis of information flow in miso neuro-spike communication channel with synaptic plasticity(Institute of Electrical and Electronics Engineers (IEEE), 2018) Ramezani H.; Muzio G.; N/A; Department of Electrical and Electronics Engineering; Khan, Tooba; Akan, Özgür Barış; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 6647Communication among neurons is the most promising technique for biocompatible nanonetworks. This necessitates the thorough communication theoretical analysis of information transmission among neurons. The information flow in neuro-spike communication channel is regulated by the ability of neurons to change their synaptic strengths over time, i.e. synaptic plasticity. Thus, the performance evaluation of the nervous nanonetwork is incomplete without considering the influence of synaptic plasticity. Hence, in this paper, we provide a comprehensive model for multiple-input single-output (MISO) neuro-spike communication by integrating the spike timing dependent plasticity (STDP) into existing channel model. We simulate this model for a realistic scenario with correlated inputs and varying spiking threshold. We show that plasticity is strengthening the correlated input synapses at the expense of weakening the synapses with uncorrelated inputs. Moreover, a nonlinear behavior in signal transmission is observed with changing spiking threshold.Publication Metadata only Analysis of single amino acid variations in singlet hot spots of protein-protein interfaces(Oxford Univ Press, 2018) N/A; N/A; Department of Computer Engineering; Department of Chemical and Biological Engineering; Özdemir, E. Sıla; Gürsoy, Attila; Keskin, Özlem; PhD Student; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 8745; 26605Motivation: Single amino acid variations (SAVs) in protein-protein interaction (PPI) sites play critical roles in diseases. PPI sites (interfaces) have a small subset of residues called hot spots that contribute significantly to the binding energy, and they may form clusters called hot regions. Singlet hot spots are the single amino acid hot spots outside of the hot regions. The distribution of SAVs on the interface residues may be related to their disease association. Results: We performed statistical and structural analyses of SAVs with literature curated experimental thermodynamics data, and demonstrated that SAVs which destabilize PPIs are more likely to be found in singlet hot spots rather than hot regions and energetically less important interface residues. In contrast, non-hot spot residues are significantly enriched in neutral SAVs, which do not affect PPI stability. Surprisingly, we observed that singlet hot spots tend to be enriched in disease-causing SAVs, while benign SAVs significantly occur in non-hot spot residues. Our work demonstrates that SAVs in singlet hot spot residues have significant effect on protein stability and function.Publication Metadata only Antitumor efficacy of ceranib-2 with nano-formulation of PEG and rosin esters(Humana Press Inc, 2021) Ben Taleb, Ali; Karakus, Selcan; Tan, Ezgi; Ilgar, Merve; Kutlu, Ozlem; Kutlu, Hatice Mehtap; Kilislioglu, Ayben; N/A; Gözüaçık, Devrim; Faculty Member; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); School of Medicine; 40248Ceranib-2 is a recently discovered, poorly water-soluble potent ceramidase inhibitor, with the ability to suppress cancer cell proliferation and delay tumor growth. However, its poor water solubility and weak cellular bioavailability hinder its use as a therapeutic agent for cancer. PEGylated rosin esters are an excellent platform as a natural polymer for drug delivery applications, especially for controlling drug release due to their degradability, biocompatibility, capability to improve solubility, and pharmacokinetics of potent drugs. In this study, stable aqueous amphiphilic submicron-sized PEG400-rosin ester-ceranib-2 (PREC-2) particles, ranging between 100 and 350 nm in a 1:1 mixture, were successfully synthesized by solvent evaporation mediated by sonication. Conclusion: Stable aqueous PEGylated rosin ester nanocarriers might present a significant solution to improve solubility, pharmacokinetic, and bioavailability of ceranib-2, and hold promises for use as an anticancer adjacent drug after further investigations.Publication Metadata only Asymmetrical relaying in molecular communications(IEEE-Inst Electrical Electronics Engineers Inc, 2022) Pusane, Ali E.; Yılmaz, H. Birkan; Tuğcu, Tuna; N/A; Department of Electrical and Electronics Engineering; Angjo, Joana; Başar, Ertuğrul; Master Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 149116Molecular communication via diffusion (MCvD) is a novel communication technique that uses the diffusive characteristics of molecules for enabling the communication between nanomachines. Since the molecules propagate following a random motion, MCvD schemes are usually limited to a short communication range. Most of the molecular relaying schemes in the literature consider symmetric setups where transmitters and receivers are placed at the same distance from the relay, which is difficult to provide in practical scenarios and a possible cause of failure. In this study, asymmetric molecular links of a relay system are investigated. In order to achieve a satisfactory overall performance in spite of the asymmetries, two parameter optimization methods are proposed for the uplink of a relaying system, based on emitting different types of molecules with different diffusion coefficient values from the transmitters. Due to the channel symmetry, the solutions presented in this study are expected to hold for the downlink as well. The resulting bit error rate (BER) performances are presented and discussed.