Home

Prof. Malik Yousefmalik

Associate Professor 
The Head of the Galilee Center for Digital Health Research (GalilDHR)   
Zefat Academic College
Data Science
Bioinformatics
Text Classification
Big Data

E-Mail: malik.yousef@gmail.com
my CV
my Google Scholar Profile
my LinkEdin

Research Statement

My general research interest encompasses the development of machine learning
techniques to resolve problems in bioinformatics/computational biology and text
classification. I am interested in applying these computational tools to the analysis of
complex and varied biomedical data, in order to establish gene-based diagnostic tests
and therapeutic strategies for improving public health, by helping to understand the
genetic foundation of diseases. These discoveries will further enable the development
of unifying global perspectives and principles in biology that can be applied to the
advancement of medical research. My postdoctoral work at the Wistar Institute
Cancer Center provided me with the opportunity to work with a number of research
groups on clinical projects ranging from the development of cancer diagnostics and
identifying potential targets to studies on infectious diseases including extensive
collaboration with investigators working on HIV. During this time, I also developed a
research program focused on identifying miRNAs and their targets.
Within bioinformatics/computational biology, my present research can be divided into
two basic domains:
 MicroRNA gene and target identification. Studying miRNAs and their targets is an
important area of research because of their role in gene expression regulation.
 Highly collaborative coding and non-coding gene expression analysis as they
relate to biomedical studies. My extensive experiences collaborating with
biomedical researchers at all levels put me in a unique position to work closely
within a diverse groups of bench scientists from varied disciplines as well as
computational researchers
The new project (big project) that I am planning to develop for gene expression
analysis is called “Crowd-sourcing gene annotation and pathology using an algorithm
guided community approach”. The aim of the project is allowing human involvement
and the wisdom of the crowd that will enhance the understanding of the outcome of
the bioinformatics tool. The user will then be exposed to a variety of opinion about his
data based on other researcher’s involvement. Additionally the system will be based
on different biological database that will be integrated in order to get the optimal list
of significant information about genes for a specific disease.
The aim of my research in the microRNA field is to combine all my research in miRNA
in one integrated system that will find the hidden message in the microRNA
sequences and their targets.