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R package ceRNAnetsim written by our lab member Selcen is alive! Please give it a spin with devtools:: install_github(\"selcenari/ceRNAnetsim\")

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Assist.Prof.Dr. Alper YILMAZ

Yildiz Technical University

Biography

Alper Yilmaz is an Assistant Professor at Yildiz Technical University. His research interest is in various topics in the field of bioinformatics. More specifically, he is interested in genome grammar (text mining in genome), next-generation sequencing analysis and analysis of gene expression via deep learning.

Short Bio: Alper Yilmaz completed his bachelor in 2000 in field of Molecular Biology and Genetics. Then he started his PhD at the Ohio State Universtiy, studied translational control of HIV mRNAs. After completing his PhD in 2007 he studied on DNA words in genomes and next-generation sequencing analysis as a post-doc in same university. He started faculty position in 2012 and is interested in genome grammar, next-generation sequencing analysis and analysis of gene expression via deep learning.

Me in one sentence: Socially awkward, distant and introvert, avid Linux user, commandline guru, fascinated with pipe (| or %>%), plain text enthusiast, excited with (R)Markdown, Docker evangelist, likes coding, Tidyverse fan, amazed with viruses, molecular biologist by training, self-taught bioinformatician, a numberphile and a computerphile.

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Interests

Genome Grammar
RNA-Seq analysis
Deep Learning in gene expression

Education

PhD in Molecular Biology, 2007

The Ohio State University
BSc in Molecular Biology and Genetics, 2000

Bilkent University

Experience

Faculty

Yildiz Technical University

Feb 2012 – Present Turkey

Dept. of Bioengineering

Post-doctoral Researcher

The Ohio State University

Jan 2008 – Dec 2011 Ohio

Conducted ChIP-Seq and RNA-Seq analysis.

Projects

ceRNAnetsim Package

MicroRNAs (miRNAs) are a family of short non-coding RNAs that are key players of post-transciptional regulations. Targets of miRNAs compete against shared miRNAs, hypothesized as competing endogenous RNAs (ceRNAs). We are working on developing network-based computational tools to bring a new perspective to complicated RNA interactions because of the complex interactions of a wide variety of RNA fragments in the cell.

Secondary Metabolite Retrosynthesis

An abstract sample of a research project.

Tissue Specific Gene Expression

Discovery of genes that are expressed specifically in few tissues only.

Deep Learning Gene Expression

An example of using the in-built project page for deep learning.

External Project

An example of linking directly to an external project website using external_link.

Internal Project

An example of using the in-built project page.

Metabolic Networks

An example of using the in-built project page.

Word Vectors

An example of using the in-built project page.

Recent & Upcoming Talks

Example Talk

An example talk using Wowchemy’s Markdown slides feature.

Jun 1, 2030 1:00 PM — 3:00 PM Wowchemy HQ

Recent Publications

Quickly discover relevant content by filtering publications.

(2019). An example preprint / working paper.

PDF Code Dataset Project Poster Slides Video Source Document Custom Link

Hatice Busra Konuk, Alper Yilmaz (2018). Breast cancer gene expression profile analysis in terms of genes specific to non-breast tissues. In ICGB.

Project

Selcen Ari, Alper Yilmaz (2018). Multifactorial Modelling of MicroRNA Associated Repression and Its Subsequent Effects on Gene Expression in MicroRNA:Target Network. In 7. International Molecular Biology and Biotechnology Congress.

Project

Alper Yilmaz (2018). Batch Analyis of RNA-Seq Data with Docker in AWS Cloud. In ICAMLS 2018 International Conference on Applied Mathematics, Modeling and Life Science Problems.

Hatice Busra Konuk, Muhammet Rasit Cesur, Alper Yilmaz (2017). What is the Relationship Between Cancer DEGs and Tissue Specific Genes. In Lisansüstü Araştırmalar Sempozyumu ve Tanıtım Günleri.

Project Video

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Featured Publications

Cem OZel, Alper Yilmaz

July 2018 In IVEK 3rd International Convention of Pharmaceuticals and Pharmacies

Prebiotics and Probiotics= Break the ‘Self-Domino Effect’ for obesity Treatment

..

Hatice Busra Konuk, Alper Yilmaz

July 2017 In International Congress on Advances in Bioscience and Biotechnology

Rigorous Identification of Tissue Specific Genes in silico

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KALYON OĞUZHAN, YILMAZ ALPER

July 2017 In IDDGC17

Survey of Chimeric mRNAs in HIV Infected Patient RNA-SEQ Data

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Elham Pashaei, Alper Yilmaz, Mustafa Ozen, Nizamettin Aydin

July 2016 In SMC

Prediction of splice site using AdaBoost with a new sequence encoding approach

The Biological sequence data are increasing rapidly, so there is a vital need of effective method for gene detection. Predicting of splice site is an important part of gene finding. Therefore, attempts to improve the prediction accuracy of the computational methods for splice sites detection continue. In this paper we propose a hybrid algorithm for splice sites prediction by combining AdaBoost classifier with a novel nucleotide encoding method, namely FDDM. Our encoding method provides frequency difference between the true sites and false sites (FD) along with distance measure (DM). The proposed method produces an improvement in comparison with the result of current methods such as MM1-SVM, Reduced MM1-SVM, SVM-B, LVMM, DM-SVM, DM2-AdaBoost and MSC+Pos(+APR)-SVM, when applied to the HS3D dataset with repeated 10-fold cross validation. In addition, for demonstrating the stability of the method, we also applied it to NN269 dataset. The obtained results indicate that the new method is practicable and efficient.