ºÝºÝߣshows by User: BilalNizami / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: BilalNizami / Tue, 23 Jul 2013 03:50:34 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: BilalNizami NEXT GENERATION SEQUENCING /slideshow/ngs-24528420/24528420 ngs-130723035034-phpapp02
Deciphering DNA sequences is essential for virtually all branches of biological research. With the advent of capillary electrophoresis (CE)-based Sanger sequencing, scientists gained the ability to elucidate genetic information from any given biological system. This technology has become widely adopted in laboratories around the world, yet has always been hampered by inherent limitations in throughput, scalability, speed, and resolution that often preclude scientists from obtaining the essential information they need for their course of study. To overcome these barriers, an entirely new technology was required—Next-Generation Sequencing (NGS), a fundamentally different approach to sequencing that triggered numerous ground-breaking discoveries and ignited a revolution in genomic science.]]>

Deciphering DNA sequences is essential for virtually all branches of biological research. With the advent of capillary electrophoresis (CE)-based Sanger sequencing, scientists gained the ability to elucidate genetic information from any given biological system. This technology has become widely adopted in laboratories around the world, yet has always been hampered by inherent limitations in throughput, scalability, speed, and resolution that often preclude scientists from obtaining the essential information they need for their course of study. To overcome these barriers, an entirely new technology was required—Next-Generation Sequencing (NGS), a fundamentally different approach to sequencing that triggered numerous ground-breaking discoveries and ignited a revolution in genomic science.]]>
Tue, 23 Jul 2013 03:50:34 GMT /slideshow/ngs-24528420/24528420 BilalNizami@slideshare.net(BilalNizami) NEXT GENERATION SEQUENCING BilalNizami Deciphering DNA sequences is essential for virtually all branches of biological research. With the advent of capillary electrophoresis (CE)-based Sanger sequencing, scientists gained the ability to elucidate genetic information from any given biological system. This technology has become widely adopted in laboratories around the world, yet has always been hampered by inherent limitations in throughput, scalability, speed, and resolution that often preclude scientists from obtaining the essential information they need for their course of study. To overcome these barriers, an entirely new technology was required—Next-Generation Sequencing (NGS), a fundamentally different approach to sequencing that triggered numerous ground-breaking discoveries and ignited a revolution in genomic science. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ngs-130723035034-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Deciphering DNA sequences is essential for virtually all branches of biological research. With the advent of capillary electrophoresis (CE)-based Sanger sequencing, scientists gained the ability to elucidate genetic information from any given biological system. This technology has become widely adopted in laboratories around the world, yet has always been hampered by inherent limitations in throughput, scalability, speed, and resolution that often preclude scientists from obtaining the essential information they need for their course of study. To overcome these barriers, an entirely new technology was required—Next-Generation Sequencing (NGS), a fundamentally different approach to sequencing that triggered numerous ground-breaking discoveries and ignited a revolution in genomic science.
NEXT GENERATION SEQUENCING from Bilal Nizami
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PREDICTION OF ANTIMICROBIAL PEPTIDES USING MACHINE LEARNING METHODS /slideshow/bilal-mbi11003/23059924 bilalmbi11003-130616070147-phpapp02
Increasing resistance toward the conventional antibiotics has become a global concern. Antimicrobial peptides (AMPs) are potential alternatives for conventional antibiotics. Due to cost related reasons in designing and synthesis of AMPs. Machine learning based prediction tools are indispensable. ]]>

Increasing resistance toward the conventional antibiotics has become a global concern. Antimicrobial peptides (AMPs) are potential alternatives for conventional antibiotics. Due to cost related reasons in designing and synthesis of AMPs. Machine learning based prediction tools are indispensable. ]]>
Sun, 16 Jun 2013 07:01:47 GMT /slideshow/bilal-mbi11003/23059924 BilalNizami@slideshare.net(BilalNizami) PREDICTION OF ANTIMICROBIAL PEPTIDES USING MACHINE LEARNING METHODS BilalNizami Increasing resistance toward the conventional antibiotics has become a global concern. Antimicrobial peptides (AMPs) are potential alternatives for conventional antibiotics. Due to cost related reasons in designing and synthesis of AMPs. Machine learning based prediction tools are indispensable. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/bilalmbi11003-130616070147-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Increasing resistance toward the conventional antibiotics has become a global concern. Antimicrobial peptides (AMPs) are potential alternatives for conventional antibiotics. Due to cost related reasons in designing and synthesis of AMPs. Machine learning based prediction tools are indispensable.
PREDICTION OF ANTIMICROBIAL PEPTIDES USING MACHINE LEARNING METHODS from Bilal Nizami
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