Self-driven web technologist and cross-platform solutions enthusiast with strong analytic mind. Interest in pattern recognition and integration between web platforms and databases. PhD and Engineering degrees in fields of chemistry / bioinformatics with a strong publication record in peer-reviewed journals. Java, Python & PHP programmer. Keen on rock music and rock climbing
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Application and implementation of probabilistic profile-profile comparison methods for protein fold recognition
Fold recognition is a method of fold detecting and protein tertiary structure prediction
applied for proteins lacking homologues sequences of known fold and structure
deposited in the Protein Data Bank. They are based on assumption that there is strictly
limited number of different protein folds in nature, mostly as a result of evolution and
due to basic physical and chemical constraints of polypeptide chains.
Fold recognition methods are useful for protein structure prediction, evolutionary
analysis, metabolic pathways and enzymatic efficiency prediction, molecular docking
and drug design.
Currently there are about 1300 discovered and characterized protein folds in SCOP and
CATH databases. Every newly discovered protein sequence has significant chances to
be classified into one of those folds. Many different approaches have been proposed for
finding the correct fold for a new sequence and it is often useful to include evolutionary
information for query as well as for target proteins. One of the methods of including this
information is a comparison of a query and target sequences profiles. These fold
recognition techniques are called profile-profile methods.
Profile-profile alignments can be calculated using a dot-product, a probabilistic model,
stochastic or theoretical measures. Here are presented applications and
implementations of probabilistic profile-profile comparison methods and advantages of
usage of probabilistic scoring function over comparable fold recognition techniques.
The purpose of this comparison is to show that probabilistic profile-profile methods may
outperform other fold recognition methods in comparison in analysis of distantly related
proteins and that they can be applied not only for fold recognition but also for slightly
different purposes like gene identification, detection of domain boundaries and
modeling of complex proteins.
Full text of my Ph.D. thesis can be downloaded here
Overview Continuous integration (CI) is a development practice which allows testing, building and checking the quality of the application in automated way without manual developer intervention. It requires developers to integrate code into a shared repository several times a day or every commit/merge to the given branch of the repository. Each check-in is then verified by an automated build, allowing teams to detect problems early. While PHP Continuous Integration (PHPCI) does not require the the code compilation as build” one can understand the set of task like testing and quality checks which are performed in timely manner or when the certain conditions are met. PHPCI can be performed on Jenkins Server. The detailed description of jenkins server configuration in is presented here. PHPCI requires PHing package which can be provided into application by Composer.
The International Supercomputing Conference is the Europe’s premier HPC event. The attendance allows observing trends science and technology of High Performance Computing for whole next year. 2009 edition achieved record numbers of attendees and exhibitors, a level of success even more impressive given the international economic crisis. With its move to Hamburg, ISC’09 reached a significantly higher level of attendance, bringing 1,670 HPC industry leaders. Research labs demonstrated their scientific applications of supercomputing in most recent fields such us GPGPU accelerators, clouds and green computing. Furthermore, this, ISC’09 also welcomed several first-time exhibitors. The exhibition brought countless highlights such as the demo of both the IS5000 40 Gb/s infniband switches and low-latency 10 Gigabit Ethernet. The attendance on ISC’09 allows to anticipate future development of ATLAS system and to present current achievements’ of ToK4nEDA team. Jakub Paś Jakub Paś Ja
We have developed a fully automated web service available for the academic community which purpose is to increase the sensitivity of the detection of distantly related protein families. Predicted secondary structure information was added to the information about sequence conservation and variability, a technique known from hybrid threading approaches. The accuracy of the meta proﬁles created this way is compared with proﬁles containing only sequence information and with the standard approach of aligning a single sequence with a proﬁle. Additionally, the alignment of meta proﬁles is more sensitive in detecting remote homology between protein families and more effective than aligning two sequence-only proﬁles or proﬁle to sequence. The speciﬁcity of the alignment score is improved in it’s lower range compared to the robust sequence-only proﬁles. ( More ) Comprehensive classification of nucleotidyltransferase fold proteins: identification of novel families and their representatives in