Research Outputs

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    PublicationOpen Access
    A compressed sensing framework for efficient dissection of neural circuits
    (Nature Publishing Group (NPG), 2019) Lee, Jeffrey B.; Yonar, Abdullah; Hallacy, Timothy; Shen, Ching-Han; Milloz, Josselin; Srinivasan, Jagan; Ramanathan, Sharad; Department of Physics; Kocabaş, Aşkın; Department of Physics; College of Sciences; 227753
    A fundamental question in neuroscience is how neural networks generate behavior. The lack of genetic tools and unique promoters to functionally manipulate specific neuronal subtypes makes it challenging to determine the roles of individual subtypes in behavior. We describe a compressed sensing-based framework in combination with non-specific genetic tools to infer candidate neurons controlling behaviors with fewer measurements than previously thought possible. We tested this framework by inferring interneuron subtypes regulating the speed of locomotion of the nematode Caenorhabditis elegans. We developed a real-time stabilization microscope for accurate long-term, high-magnification imaging and targeted perturbation of neural activity in freely moving animals to validate our inferences. We show that a circuit of three interconnected interneuron subtypes, RMG, AVB and SIA control different aspects of locomotion speed as the animal navigates its environment. Our work suggests that compressed sensing approaches can be used to identify key nodes in complex biological networks.
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    Publication
    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; 51269
    Genetically 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.
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    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; 149116
    Molecular 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.
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    PublicationOpen Access
    Classification of drug molecules considering their IC(50) values using mixed-integer linear programming based hyper-boxes method
    (BioMed Central, 2008) Department of Industrial Engineering; Department of Chemical and Biological Engineering; Armutlu, Pelin; Özdemir, Muhittin Emre; Yüksektepe, Fadime Üney; Kavaklı, İbrahim Halil; Türkay, Metin; Faculty Member; Department of Industrial Engineering; Department of Chemical and Biological Engineering; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; N/A; N/A; N/A; 40319; 24956
    Background: A priori analysis of the activity of drugs on the target protein by computational approaches can be useful in narrowing down drug candidates for further experimental tests. Currently, there are a large number of computational methods that predict the activity of drugs on proteins. In this study, we approach the activity prediction problem as a classification problem and, we aim to improve the classification accuracy by introducing an algorithm that combines partial least squares regression with mixed-integer programming based hyper-boxes classification method, where drug molecules are classified as low active or high active regarding their binding activity (IC(50) values) on target proteins. We also aim to determine the most significant molecular descriptors for the drug molecules. Results: We first apply our approach by analyzing the activities of widely known inhibitor datasets including Acetylcholinesterase (ACHE), Benzodiazepine Receptor (BZR), Dihydrofolate Reductase (DHFR), Cyclooxygenase-2 (COX-2) with known IC(50) values. The results at this stage proved that our approach consistently gives better classification accuracies compared to 63 other reported classification methods such as SVM, Naive Bayes, where we were able to predict the experimentally determined IC50 values with a worst case accuracy of 96%. To further test applicability of this approach we first created dataset for Cytochrome P450 C17 inhibitors and then predicted their activities with 100% accuracy. Conclusion: Our results indicate that this approach can be utilized to predict the inhibitory effects of inhibitors based on their molecular descriptors. This approach will not only enhance drug discovery process, but also save time and resources committed.
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    CRISPR-CAS13 system as a promising and versatile tool for cancer diagnosis, therapy, and research
    (American Chemical Society (ACS), 2021) Palaz, Fahreddin; Kalkan, Ali Kerem; Demir, Ayca Nur; Tozluyurt, Abdullah; Ozcan, Ahsen; Ozsoz, Mehmet; Department of Molecular Biology and Genetics; Can, Özgür; Undergraduate Student; Department of Molecular Biology and Genetics; College of Sciences; N/A
    Over the past decades, significant progress has been made in targeted cancer therapy. In precision oncology, molecular profiling of cancer patients enables the use of targeted cancer therapeutics. However, current diagnostic methods for molecular analysis of cancer are costly and require sophisticated equipment. Moreover, targeted cancer therapeutics such as monoclonal antibodies and small-molecule drugs may cause off-target effects and they are available for only a minority of cancer driver proteins. Therefore, there is still a need for versatile, efficient, and precise tools for cancer diagnostics and targeted cancer treatment. In recent years, the CRISPR-based genome and transcriptome engineering toolbox has expanded rapidly. Particularly, the RNA-targeting CRISPR-Cas13 system has unique biochemical properties, making Cas13 a promising tool for cancer diagnosis, therapy, and research. Cas13-based diagnostic methods allow early detection and monitoring of cancer markers from liquid biopsy samples without the need for complex instrumentation. In addition, Cas13 can be used for targeted cancer therapy through degrading and manipulating cancer-associated transcripts with high efficiency and specificity. Moreover, Cas13-mediated programmable RNA manipulation tools offer invaluable opportunities for cancer research, identification of drug-resistance mechanisms, and discovery of novel therapeutic targets. Here, we review and discuss the current use and potential applications of the CRISPR-Cas13 system in cancer diagnosis, therapy, and research. Thus, researchers will gain a deep understanding of CRISPR-Cas13 technologies, which have the potential to be used as next-generation cancer diagnostics and therapeutics.
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    PublicationOpen Access
    Machine learning helps identify CHRONO as a circadian clock component
    (Public Library of Science, 2014) Anafi, Ron C.; Lee, Yoo; Sato, Trey K.; Venkataraman, Anand; Ramanathan, Chidambaram; Hughes, Michael E.; Baggs, Julie E.; Growe, Jacqueline; Liu, Andrew C.; Kim, Junhyong; Hogenesch, John B.; Kavaklı, İbrahim Halil; Faculty Member; College of Engineering; 40319
    Over the last decades, researchers have characterized a set of ‘‘clock genes’’ that drive daily rhythms in physiology and behavior. This arduous work has yielded results with far-reaching consequences in metabolic, psychiatric, and neoplastic disorders. Recent attempts to expand our understanding of circadian regulation have moved beyond the mutagenesis screens that identified the first clock components, employing higher throughput genomic and proteomic techniques. In order to further accelerate clock gene discovery, we utilized a computer-assisted approach to identify and prioritize candidate clock components. We used a simple form of probabilistic machine learning to integrate biologically relevant, genome-scale data and ranked genes on their similarity to known clock components. We then used a secondary experimental screen to characterize the top candidates. We found that several physically interact with known clock components in a mammalian two-hybrid screen and modulate in vitro cellular rhythms in an immortalized mouse fibroblast line (NIH 3T3). One candidate, Gene Model 129, interacts with BMAL1 and functionally represses the key driver of molecular rhythms, the BMAL1/CLOCK transcriptional complex. Given these results, we have renamed the gene CHRONO (computationally highlighted repressor of the network oscillator). Bi-molecular fluorescence complementation and co-immunoprecipitation demonstrate that CHRONO represses by abrogating the binding of BMAL1 to its transcriptional co-activator CBP. Most importantly, CHRONO knockout mice display a prolonged free-running circadian period similar to, or more drastic than, six other clock components. We conclude that CHRONO is a functional clock component providing a new layer of control on circadian molecular dynamics.
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    Rapid diagnosis of spinal muscular atrophy using tetra-primer ARMS PCR assay: Simultaneous detection of SMN1 and SMN2 deletion
    (Elsevier, 2010) Etlik, Ozdal; Koksal, Vedat; Arican-Baris, S. Tugba; Department of Molecular Biology and Genetics; Barış, İbrahim; Teaching Faculty; Department of Molecular Biology and Genetics; College of Sciences; 111629
    Spinal muscular atrophy (SMA), the leading genetic cause of death in childhood, is an autosomal recessive neuromuscular disorder characterized by progressive muscle weakness, associated with deletions of the survival motor neuron 1 (SMN1) gene. Approximately 94% of SMA patients carry homologous deletions of SMN1 exon(s) 7 (and 8). Because of the high incidence and severity of the disease, precise detection and quantification of SMN1 and SMN2 gene copy numbers is essential for diagnosis and genetic counseling. We have developed a reliable single-tube tetra-primer PCR assay to simultaneously detect both the SMN1 and SMN2 exon 7 deletion using the advantage of C/T difference at nucleotide position of 840 in exon 7. The assay has been optimized and tested in 48 healthy controls, 20 known patients with SMA, 12 carriers (one SMN1 copy), and 8 amniotic fluids suspected of having SMA for whom we had determined the SMN1/SMN2 deletion by an additional PCR-RFLP method. We have observed complete concordance between methods. Our tetra-primer PCR assay is sensitive, low-cost, and easy to use method for simultaneous detection of both SMN1 and SMN2 deletion, which could be used even in "low-tech" laboratories.
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    SYBR green dye-based probe-free SNP genotyping: Introduction of T-Plex real-time PCR assay
    (Elsevier, 2013) Etlik, Ozdal; Koksal, Vedat; Ocak, Zeynep; Baris, Saniye Tugba; Department of Molecular Biology and Genetics; Barış, İbrahim; Teaching Faculty; Department of Molecular Biology and Genetics; College of Sciences; 111629
    Single-nucleotide polymorphism (SNP) genotyping is widely used in genetic association studies to characterize genetic factors underlying inherited traits. Despite many recent advances in high-throughput SNP genotyping, inexpensive and flexible methods with reasonable throughput levels are still needed. Real-time PCR methods for discovering and genotyping SNPs are becoming increasingly important in various fields of biology. In this study, we introduce a new, single-tube strategy that combines the tetra-primer ARMS PCR assay, SYBR Green I-based real-time PCR, and melting-point analysis with primer design strategies to detect the SNP of interest. This assay, T-Plex real-time PCR, is based on the T. discrimination of the amplified allele-specific amplicons in a single tube. The specificity, sensitivity, and robustness of the assay were evaluated for common mutations in the FV, PII, MTHFR, and FGFR3 genes. We believe that T-Plex real-time PCR would be a useful alternative for either individual genotyping requests or large epidemiological studies.