M4B: A novel method for designing and ordering of the genetic devices

Date

2012-06-29

Author

Hashemikhabir, Seyedsasan
Ersoy, Gokhan
Oguz, Gokce
Yaldiz, Burcu
Tuncel, Yener
Budak, Gungor
Karaaslan, Saygin
Aydın Son, Yeşim
Can, Tolga

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

157
views

0
downloads

In synthetic biology, designing a new genetic construct demands in-detail studies of its candidate components individually and in a composition with each other. These costly wet lab experiments require considerable amount of time and usually result in undesired output. In this paper, we propose a method for the extraction of existing or novel synthetic devices from the available biological parts or devices from iGEMs BioParts Registry and ordered the resulting devices based on their computed reliabilities. This method is very efficient and it helps the wetlab biologists in designing their genetic devices based on the given input and output in a reasonable amount of time. This method is implemented in "Mining for BioBricks" (M4B), a web-based application that facilitates the prediction of novel genetically made devices based on the given input and output. © 2012 IEEE.

URI

https://hdl.handle.net/11511/69790

DOI

https://doi.org/10.1109/hibit.2012.6209054

Collections

Graduate School of Informatics, Conference / Seminar

Suggestions

OpenMETU
Core

GLANET: genomic loci annotation and enrichment tool Otlu, Burcak; Firtina, Can; Keles, Sunduz; Tastan, Oznur (Oxford University Press (OUP), 2017-09-15) Motivation: Genomic studies identify genomic loci representing genetic variations, transcription factor (TF) occupancy, or histone modification through next generation sequencing (NGS) technologies. Interpreting these loci requires evaluating them with known genomic and epigenomic annotations.
A Review on Data Mining and Continuous Optimization Applications in Computational Biology and Medicine Weber, Gerhard Wilhelm; Ozogur-Akyuz, Sureyya; Kropat, Erik (2009-06-01) An emerging research area in computational biology and biotechnology is devoted to mathematical modeling and prediction of gene-expression patterns; it nowadays requests mathematics to deeply understand its foundations. This article surveys data mining and machine learning methods for an analysis of complex systems in computational biology, It mathematically deepens recent advances in modeling and prediction by rigorously introducing the environment and aspects of errors and uncertainty into the genetic con...
On optimization, dynamics and uncertainty: A tutorial for gene-environment networks WEBER, G. -W.; Uğur, Ömür; Taylan, P.; TEZEL, AYSUN (2009-05-28) An emerging research area in computational biology and biotechnology is devoted to mathematical modeling and prediction of gene-expression patterns; to fully understand its foundations requires a mathematical study. This paper surveys and mathematically expands recent advances in modeling and prediction by rigorously introducing the environment and aspects of errors and uncertainty into the genetic context within the framework of matrix and interval arithmetic. Given the data from DNA microarray experiments...
Mathematical contributions to dynamics and optimization of gene-environment networks Weber, Gerhard Wilhelm; Tezel, Aysun; TAYLAN, PAKİZE; Soyler, Alper; Cetin, Mehmet (Informa UK Limited, 2008-01-01) This article contributes to a further introduction of continuous optimization in the field of computational biology which is one of the most challenging and emerging areas of science, in addition to foundations presented and the state-of-the-art displayed in [C.A. Floudas and P.M. Pardalos, eds., Optimization in Computational Chemistry and Molecular Biology: Local and Global Approaches, Kluwer Academic Publishers, Boston, 2000]. Based on a summary of earlier works by the coauthors and their colleagues, it r...
Using Adaptive Neuro-Fuzzy Inference System for Classification of Microarray Gene Expression Cancer Profiles Haznedar, Bülent; Arslan, Mustafa Turan; Kalınlı, Adem (2018-05-01) Microarray is a technology that enables simultaneously analysis of thousands of genes in DNA structure depending on the advances in biochemistry. With this technology, it has become possible to diagnose and treat heredity diseases by analyzing thousands of gene expression levels. This study proposes an artificial intelligence method, Adaptive neuro-fuzzy inference system (ANFIS), to classify cancer gene expression profiles. The findings obtained with the proposed ANFIS approach are compared with the results...

Citation Formats

S. Hashemikhabir et al., “M4B: A novel method for designing and ordering of the genetic devices,” 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/69790.