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Incorporation of pathway knowledge into microarray analysis has been favoured by researchers owing to the improved biological interpretation of the analysis outcome. However, most of the pathway data are manually curated without specific biological context. Inclusion of non-informative genes in the analysis of context specific microarray data could lead to classifier with poor discriminative power. Thus, one of the main challenges is how to effectively identify informative genes from the pathway data. This paper proposes a firefly optimised penalised support vector machine with SCADL2 penalty function (SVM-SCADL2-FFA) in optimising tuning parameters for each pathway for efficient identification of informative genes and pathways. Experiments are done on lung cancer and gender data sets. Tenfold CV is used to evaluate the performance in terms of accuracy, specificity, sensitivity and F-score. The identified informative genes are validated through online databases. Our proposed method shows consistent improvements compared to previous works.

Pensyarah FKEE UMP Kongsi Kepakaran Dalam Pengaturcaraan dan Pembinaan Lego Mindstrom

Pekan 23 Februari - Fakulti Kejuruteraan Elektrik dan Elektronik (FKEE) Universiti Malaysia Pahang (UMP) dengan kerjasama Pejabat Pendidikan Daerah Pekan (PPD) menganjurkan Bengkel Traning of Trainers (TOT), Pekan baru-baru ini.

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Innovate 2017 - the STEM EcoSystem

UMP Pekan 14 July - As the Pahang State Level host for this year’s championship, we welcome you to the 2017 Young Innovate Malaysia Competition. YI 2017 provides a highly competitive platform for academicians, teachers, industries and most importantly the future generation - our school children.

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On 17th May 2017, 20 of the faculty staffs were involved in “Santai Sains Bersama FKEE”: a STEM outreach program at Sek. Keb. Sri Maulana in Pekan, Pahang. This is.

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Program GTEX ENHANCING GRADUATE SKILLS TOWARDS EMPLOYABILITY ini merupakan program persedian kepada pelajar universiti tahun akhir yang bakal melalui alam pekerjaan.

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