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More students joining BCB in Fall 2017

A total of eight students will be joining BCB this fall to pursue their PhD degrees.  Here are three students who will be joining from overseas:

Shofi Andari

Malang, Indonesia


BS and MS in Statistics

Institut Pertanian Bogor

Institut Teknologi Sepuluh Nop

Google Scholar:



he is interested in structural bioinformatics, comparative Genetics and transcriptomics.

In her Undergraduate work, she worked on a thesis project titled: A study of clustering methods on mixed numerical and categorical data.

In her Master’s work, she worked on a these project titled: Breast cancer diagnosis using smooth support vector machine and multivariate adaptive regression splines.

From 2013 to present, Shofi has been a lecturer in the Department of Statistics at ITS in Surabaya, Indonesia where she has written books and modules, done research and given service to the community.  Courses taught included:

  • Stochastic processes - 2015 – 2016
  • Numerical methods - 2014 – 2016
  • Probability theory - 2015
  • Artificial Neural Network - 2014
  • Multivariate analysis - 2014
  • Regression analysis - 2013
  • Linear algebra - 2013
  • Introduction to computer science – 2013


Pratnya P. Oktaviana and Shofi Andari (2015). Metode Statistika Menggunakan SAS® (Statistical Method using SAS®), published by ITSPress.



• Santi W. Purnami, Shofi Andari, and Yuniati D. Pertiwi (2015). Combine sampling support vector machine for imbalanced data classification, Procedia Computer Science 72 , url:


• Shofi Andari and Santi W. Purnami (2015). Reduced Support Vector Machine Based on Nonhierarchical Clustering Techniques for Classifying Mixed Large-Scale Datasets, International Journal of Applied Mathematics and Statistics (IJAMAS) Vol. 53 (5), url:

• Bambang W. Otok, Santi W. Purnami, and Shofi Andari (2015). Developing measurement model using Bayesian confirmatory factor analysis in suppressing maternal mortality, International Journal of Applied Mathematics and Statistics (IJAMAS) Vol. 53 (6), url:



• Shofi Andari and Santi W. Purnami (2014). Classifying large-scale categorical datasets using reduce support vector machine based on clustering technique, paper was presented at ICBEta 2014 (International Conference on Biomedical Engineering Technology and Application), in Yogyakarta, Indonesia and published on its proceeding.

• Shofi Andari and Dian Anggraeni (2012). Cluster Validation in Correlated Simulation Data Using R Package clValid, paper was included as poster presentation at BaSic Science 2012 in Malang, Indonesia.

• Shofi Andari, Santi W. Purnami, and Bambang W. Otok (2012). Breast cancer diagnosis using smooth support vector machine and multivariate adaptive regression splines, paper was included as poster presentation at ICMSA 2012 (International Conference on Mathematics, Statistics, and Its Applications 2012) in Bali, Indonesia and published on its proceeding.


Professional Licensure and Certifications

2016 - Dept. of Statistics IPB, Bogor, Indonesia

Workshop on Big Data Analytics: Applications to Modern Genetics


2015 - Multidisciplinary Graduate Program

University of Indonesia, Jakarta, Indonesia

Workshop on Bioinformatics and Computational Biology


2015 - Dept. of Electrical Engineering

University of Indonesia, Depok, Indonesia

Big Data Engineer (certified by TUV Rheinland)


Research Activities

--Reduced support vector machine based on clustering techniques for large-scale datasets classification (2014, completed)

Principal investigator

Funded by: ITS Institution Local Funding, Beginner Researcher Scheme

(PNBP ITS – Penelitian Pemula)

--Smoking behavior mapping on adolescent using model based clustering approach (2014, completed)

Principal investigator

Funded by: Advanced Analysis, Ministry of Health of Indonesia

(Analisis Lanjut, Litbangkes Depkes RI)

--Feature selection based on support vector machine for microarray data application (2016, in progress)

Principal investigator

Funded by: ITS Institution Local Funding, Beginner Researcher Scheme

(PNBP ITS – Penelitian Pemula)

--Predicting survival of cervical cancer based on support vector machine and Bayesian survival analysis (2016, in progress)


Funded by: Publication and International Collaboration Grant, DIKTI

--Classification on high dimensional and imbalance data using hybrid support vector machine (2016, in progress)


Funded by: Competence Grant, DIKTI

--Classification on high dimensional and imbalance data using hybrid support vector machine (2016, in progress)


Funded by: Competence Grant, DIKTI

Professional Membership

International Society of Computational Biology (ISCB)

since 11 February 2016

Pranav Khade

Pune, MH, India

B.Sc in Biotechnology from University of Pune

M.Sc in Bioinformatics from University of Pune

Pranav Khade


As a young researcher, I am exploring different areas/domains of computational biology to identify my niche. I love the blend of research and software development and I am looking forward towards applications of statistical modeling, machine learning (specially AI and deep learning), parallel computing and optimization algorithms to raise, study and answer the challenging biological questions.



1. Master's Project: (~12 Months)

Name: Graphically Accelerated CUDA based Systematic Conformer Generation Method.

Guide: Dr. Manali Joshi, University of Pune.

Area: Cheminformatics

Nature: Tool

The tool is written in C++ and also ported on JAVA using SWIG bindings provided by OpenBabel. The tool focuses on systematic conformer generation of small molecules. The serial program is written, but now I attempt to port it on GPU (NVIDIA TESLA K20) using OpenACC and also on HADOOP in order to cater computational intensity. Along with this, my program is being redesigned to use multithreading using OpenMP and GNU Parallel. This project helped me to gain strong background of parallel computing and Object oriented programming using different libraries which can be proved useful even for different fields where parallel computing can be adapted. Along with this, I have built a database using my own text mining Perl LWP scripts to test the tool performance.


2. Model for Identification of Antimicrobial Peptides.

Guide: Dr. Valadi Jayraman

Area: Data Mining and Analysis.

Nature: Analysis

I have also worked on a machine learning project where I was leading a team of eight members. Like any other machine learning project, it involved text mining (I used Perl LWP) followed by feature extraction where I personally tested and used different APIs (such as Discovery studio API and more) followed by Model building using WEKA, LIBSVM and randomForest (R). I also worked on model refinement by doing grid search.


  •          Operating systems:  UNIX, Linux, Windows.
  •          Development & Scripting: C, C++, Java, Perl, R, Python.
  •          Web Implementation: HTML, PHP, SQL.
  •          GPU/Parallel libraries: OpenMP, OpenACC
  •          Bioinformatics Skills: Data Mining, Optimization Algorithms, Cheminformatics, Machine Learning, High performance computing, Software development, Drug discovery, Data Analysis, Classification Problems, Multiomics study.

Honors and Awards

1. DBT Fellowship: (For Semester 1 & 2)

Awarded by: Department of Biotechnology, Government of India.

For each semester of M.Sc, first fifteen students are awarded with monthly fellowship.

2. IGIB-GNR Scholarship: (For Semester 3 & 4)

Awarded by: IGIB(Institute of Genomics and Integrative Biology), Delhi

For each semester of M.Sc, first five excellent performers are awarded with this scholarship.

3. IIT GeneRations 2014 Gold Medal

Awarded by: Department of Biosciences & Bioengineering , IIT BOMBAY.

A national level quiz competition.

Zerui Zhang

Research Interests: Statistical genetics and sequence analysis

Faculty Mentioned: Dekkers, Dorman

University Attended, Major pursued:

Tsinghua University, Biological Sciences

Beijing, China    


Zerui is interested in statistical genetics and sequence analysis, clinical experiments design and data analysis. Faculty mentioned include Dekkers and Dorman.


Research experiences


Enrichment of low-abundance genes by engineered ttAgo - Aug 2015 - present

Research student (RA), Supervisor: Haitao LI, professor at Medical School, Tsinghua University

- Took charge of the TtAgo experiment, modified the purification of TtAgo; succeeded increasing enriching efficiency of low-abundance long noncoding RNA.

 - Proved the interaction effectiveness of ttAgo-gDNA-mRNA using negative gel electrophoresis and QPCR.

- Summarized the process and results, wrote a report, and gave a presentation; won Third Prize at the 34th THU Challenge Cup.


Gerontology research on nutrient promotion and the influence of diabetes - Mar 2016 - present

Intern, Employer: Ping ZENG, researcher at Dept. of Epidemiology, Beijing Hospital and Beijing Institute of Geriatrics

- Collected data on nutrient intake and health conditions of elderly in China, used graphs to depict information, wrote a proposal for the China Ministry of Health about nutritional improvements amongst the elderly.

-  Cleansed clinical data of those aged 65 and above including indexes from complete blood count and physical examinations; applied K-Nearest Neighbor to estimate the missing values.

- Analyze and indicate the possible relationships between BMI, self-help skill index and blood glucose level.


Regulation of transcriptional factors and signaling pathways in stomach development – July 4 – August 28, 2016

Summer student, Supervisor: Tae-Hee KIM, assistant professor at Dept. of Molecular Genetics, University of Toronto

- Prepared section blocks through dissecting embryos of mice with specific genes disrupted, and embedding the tissues with wax; completed the sections and staining in order to observe the influences of mutations on the stomach.

- Found the difference in thickness of smooth muscle layers in mice with disrupted Hedgehog signaling pathway; collected 3 sets of data including WT and mutant, and proved the significance of smooth muscle reduction.

- Presented experiment results using a poster at the Tsinghua-Bayer Life Science Forum in 2016.


The influence of KIF5B on mitochondrial tubulation - Aug 2014 - May 2015

RA, Supervisor: Li YU, professor at School of Life Science, Tsinghua University

- To confirm the requirement of KIF5B for mitochondrial tubulation, I purified plasmids with no KIF5B and inducible KIF5B, and helped collect confocal images of the tubulation process.

- Incubated rat NK cells and set the optimal time of cell propagation.

-  Co-authored and published "Dynamic tubulation of mitochondria drives mitochondrial network formation"on Cell Research.




Basic biological experiment skills: biochemistry, molecular biology, cellular biology, genetics and histology.

Computational skills: C, R, SPSS and SAS.