Data mining commonly involves four classes of tasks:

• Classification - Arranges the data into predefined groups. For example, an email program might attempt to classify an email as legitimate or spam. Common algorithms include decision tree learning, nearest neighbor, naive Bayesian classification and neural networks.
• Clustering - Is like classification but the groups are not predefined, so the algorithm will try to group similar items together.
• Regression - Attempts to find a function which models the data with the least error.
• Association rule learning - Searches for relationships between variables. For example a supermarket might gather data on customer purchasing habits. Using association rule learning, the supermarket can determine which products are frequently bought together and use this information for marketing purposes. This is sometimes referred to as market basket analysis.
• From experience, I can say that is one of the most frustrating positions to be in. Data mining is a huge field and can easily be bewildering for a beginner. However, high through-put techniques in molecular biology require, more and more, that bioinformatics is required to interpret the data. Furthermore, people working in bioinformatics generally come from computer science, or biology backgrounds. Data mining, however, involves statistics to one degree or another, which means entering a field that is may not be your strong point.
• Excel is fine for creating graphs. If you’re serious about data mining though, you’ll need something more heavy weight. I use R, free, and with good data mining packages such as vegan and labdsv. For beginners R can be impenetrable, I recommend this book an introduction to R as well as the underlying statistics.
• Any of us can rush head on into a land of support vector machines, hidden markov models and neural networks. But coming back to the first point, what are you trying to prove? Always question what are you doing, how does it fit in to the wider picture? Try to regularly review, and keep track of where you are going? This will prevent you from falling into data mining despair.

Data Mining Resources on the net:

A laboratory of data mining and bioinformatics is headed by Prof. Ambuj Singh. There are currently seven graduate students in the research group. Our research focuses on image informatics and scalable querying and mining of graphs.For more detail visit: http://www.cs.ucsb.edu/~dbl/

Here are the materials (Lecture notes) from several past courses on data mining and/or Web mining by Stanford: For detail visit: http://infolab.stanford.edu/~ullman/mining/mining.html
Statistical Data Mining Tutorial Slides by Andrew Moore The following links point to a set of tutorials on many aspects of statistical data mining, including the foundations of probability, the foundations of statistical data analysis, and most of the classic machine learning and data mining algorithms. For detail visit: http://www.autonlab.org/tutorials/

A tutorial on Introduction to Data Mining for Discovering hidden value in your data warehouse:http://www.thearling.com/text/dmwhite/dmwhite.htm 
Wiki Links: http://en.wikipedia.org/wiki/Data_mining
Bioinformatics with Clementine http://www.spss.ch/upload/1051192224_inseratClemBio.pdf 
Causal Data Mining in Bioinformatics by Ioannis Tsamardinos: http://www.forth.gr/ics/bmi/In_the_News/2007/EN69-4.pdf

Report on ACM Text Mining in Bioinformatics (TMBIO 006) http://www.sigir.org/forum/2007J/2007j_sigirforum_song.pdf 
BIOKDD 2002: Recent Advances in Data Mining for 
Bioinformatics: http://www.acm.org/sigs/sigkdd/explorations/issue4-2/zaki.pdf

Bioinformatics and Medical Informatics: 

Tools for Mining and Applying Genetic Information in Patient Care:http://www.biomedtechalliance.org/pdfs/03_03_05/03_03_05.pdf

DATA MINING OF MICROARRAY DATABASES FOR HUMAN LUNG CANCER: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.106.385&rep=rep1&type=pdf

Towards knowledge-based gene expression data mining: http://www.ailab.si/blaz/papers/2007-JBI-BellazziZupan.pdf

DRAFT Accepted for publication in 'Data Mining in Bioinformatics'
Jason Wang, Mohammed Zaki, Hannu Toivonen, and Dennis Shasha (Eds.), Springer:http://www.cs.helsinki.fi/u/htoivone/pubs/gene_mapping_by_pattern_discovery.pdf

Data Mining and Text Mining for Bioinformatics: Proceedings of the European Workshop: http://www.rok.informatik.hu-berlin.de/wbi/research/publications/2003/proceedings_ws_mining.pdf

Biological Network Analysis:

Graph Mining in Bioinformatics: http://agbs.kyb.tuebingen.mpg.de/wikis/bg/BNA-5.pdf.

Text mining in bioinformatics: http://agbs.kyb.tuebingen.mpg.de/wikis/bg/4.pdf

Some datamining books that are available on google books:

Data mining and bioinformatics: first international workshop, VDMB 2006 By Mehmet M. Dalkilic

Data mining: concepts and techniques By Jiawei Han, Micheline Kamber

https://github.com/jennomics/WorkflowPaper/blob/master/Genome%20Assembly%20and%20Annotation.md

Address of the bookmark: http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/

It takes FASTA DNA sequence as input, and write GFF3 as output. It uses the new NHMMER tool that comes with HMMER 3.1 for HMM searching in RNA:DNA style. NHMMER binaries for 64-bit Linux and Mac OS X are included and will be auto-detected. Multithreading is supported and one can expect roughly linear speed-ups with more CPUs. 

Address of the bookmark: https://github.com/tseemann/barrnap

Research with the help of bioinformatics with a trans-disciplinary approach is yielding good results.

http://www.thehindu.com/features/education/research/research-with-help-of-bioinformatics-helpful/article2295629.ece

JRF/SRF / Project Assistant-II recruitment in National Agri-Food Biotechnology Institute (NABI)

Essential Qualification: According to the DST (DST OM No.SR/S9/Z-09/2012 dated 21.10.2014) Post Graduate degree in basic science(M.Sc) in Bioinformatics/Computational Biology/Systems Biology/Information Technology with NET or Graduate degree in professional course with NET or Post Graduate Degree (M.Tech) in professional course in Bioinformatics/Computational Biology/Systems Biology/Information Technology. Desirable qualification/skills: 1) Should be proficient in programming in Perl/Python/R language etc. 2) Should have knowledge and skills for data mining in biological sequence database . sequence analysis tools/packages, NGS Analysis . 3) Should have knowledge and skills to work in linux environment and write shell scripts.

Age : 28 years

Hiring Process : Written-test
Job Role : Research/JRF/SRF
How to apply

Application should be sent to Administrative officer, National Agri-Food Biotechnology Institute, Knowledge City, Sector-81, Mohali so as to reach latest by 30.05.2017 before 5:30 pm.

More at http://www.nabi.res.in/Vacancies/NABI/ResearchFellowships/JRFSRFRA/2017/ADVT.%20No%202017Researcher%20(02)/ApplicationForm.pdf

http://www.disi.unige.it/person/MasulliF/ricerca/PhDinGenova2017.html

The call for some funded positions for the 3 years PhD studies at the Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS) in Genova is available at

http://www.studenti.unige.it/postlaurea/dottorati/XXXIII/ENG/

The deadline for applications is June13, 2017 and the PhD courses and fellowships should start on Nov 2017.

Details for the application to the PhD Program in Computer Science and Systems Engineering (CODICE 6608) are at http://phd.dibris.unige.it/csse/index.php/how-to-apply

The research activity of my research group is focused on Computational Intelligence, Machine Learning, Bioinformatics, Systems Biology, and Positive Technology as described at http://www.disi.unige.it/person/MasulliF/ricerca/index.html

The research themes proposed by me and Prof. Stefano Rovetta are:

- Computational Intelligence and Machine Learning (see http://www.disi.unige.it/person/MasulliF/ricerca/Phd2017-T1.html)

- Computational Intelligence and Health and Wellbeing Support( see http://www.disi.unige.it/person/MasulliF/ricerca/Phd2017-T3.html)

You can also propose a different research theme belonging to the research activity of my group.

Looking for self-motivated PhD candidates, interested to the mathematical aspects of their research and to the development of new algorithms for intelligent data analysis, and skilled in programming and in thorough experimental data analysis. They will be part of my research group and will collaborate to our research projects and publications.

Italian and international students interested to work are invited to send their cv and the name/email-addresses of 3 referees to my email address francesco.masulli@unige.it A.S.A.P.

Advertisement No. 137/ESTB/NIBMG/17-18

Position available Project Description: Several positions are available for the project titled: “A unified web-portal for analysis, integration and visualization of multi-omics data”. The goal of this project is to develop a user-accessible resource for integrated analysis and visualization of multi-OMICs data sets (including gene expression, genotype, methylation, microRNA, etc.). Data sets generated on various platforms shall be maintained in a stable database, accessed through standard querying mechanisms, and the results shall be displayed via user-friendly interface. The analysis engine shall run on open-source software (such as R/Bioconductor) developed in-house. All positions are contractual.

Appointment will be initially given for a period of one year which is extendable depending upon performance, availability of funds and requirements of the institute.

Project Code: 20275 Position: (No. of positions available)

Research Associate (3)

Position 1: Ph.D. or equivalent in statistics, computer science, mathematics, bioinformatics, or related subject.
Position 1: Those with experience in database management shall be preferred. Experience with UNIX or GNU/Linux operating system.
Position 1: Creation and maintenance of a database for population- and diseaseassociated variation resource. Development of programmatic interface for querying the database, filtering of the results and identification of genes of interest.

Rs. 36000/- + 10% HRA

Please apply online via web link http://apply.nibmg.ac.in/ (no other form of application will be accepted). The last date of application is 14-08-2017. All letters to attend screening test and /or interview will be sent only to the short-listed candidates by Email only. No correspondence will be made with applicants who are not shortlisted /not called for screening test and /or interview. No TA/DA will be paid for attending the screening test and /or interview.
Detail information at http://www.nibmg.ac.in/academic/Advt_20275.pdf

More Info: http://www.nibmg.ac.in/?q=Project%20Linked%20Personnel

SciGenom Research Foundation (SGRF) and Institute of Genomics and Integrative Biology (IGIB) are pleased to host the Next-Generation Sequencing and Bioinformatics for Genomics & Healthcare conference.

In the ten years since the first human reference genome was completed for US$3 billion the sequencing technologies have radically changed leading to great reduction in sequencing cost. Today a human genome can be sequenced for under US$ 5000 in less than two weeks. It is expected that by the end of 2015 the cost of sequencing a human genome will drop to below thousand dollars. The next generation sequencing technologies over the past five years have enabled a large number of genomic studies that impact human health and disease. Also, this has made possible the growth of microbial, animal and plant genomics studies. While the data production has increased at a rapid pace challenges remain in analyzing and understanding the data. The conference will cover the next generation sequencing (NGS) technologies, bioinformatics for NGS and applications of NGS in many areas including personalized medicine.

For more info : http://www.scigenomconferences.com/2013/default.php

Address of the bookmark: https://rob-p.github.io/CSE549F16/lectures/

Candidates must have: a PhD degree in statistics, biostatistics or bioinformatics, extensive experience in analyzing high-dimensional data (microarray, SNP, CNVs) and of validation approaches. In addition, experience in penalized regression methods, data base manipulation; and strong programming skills in order to conduct Monte Carlo studies and applications (R). Candidate must have excellent communication skills (verbal, written and presentation), a strong proficiency in Linux system.

This position is available immediately and will be filled as soon as possible. Appointment could be extended beyond the first year based on additional funding.

For more information about the Department of Biostatistics and Bioinformatics, please visit our website: http://www.biostat.duke.edu.

For more info: http://biostat.duke.edu/sites/biostat.duke.edu/files/Halabi%20-%20Postdoc%20Job%20Posting%202013%20updated.pdf

Duke University is an Equal Opportunity/Affirmative Action Employer.