BOL: Related items

Computer Theory & Genetics: George Chao at TEDxUMNSalon

Thu, 15 Aug 2013 22:08:10 -0500

George Chao is an undergraduate senior studying Genetics and Computer Science at the University of Minnesota. Having started genetics research as soon as he entered the university, he has worked in labs spanning multiple disciplines as well as in Japan. Some of these researches include developmental genetics in Drosophila, computational techniques for analyzing protein interactions, and helping with the development of algorithms to analyze motion capture data of patients with neck pain. During this time, George steadily developed a fascination with the field of bioinformatics, the study of using computational techniques to learn from genetic data. He would like to go into a career of research into the application of bioinformatics in various fields. ---- The individuals involved with TEDxUMN have a passion for bringing together the great thinkers at the University of Minnesota and giving them the opportunity to share their ideas worth spreading and to discuss our shared future. We provide these great people the opportunity to share these ideas on a global stage and with an incredibly diverse audience. We believe in the power of ideas to change attitudes, lives and ultimately the world. Check out TEDxUMN at http://www.TEDxUMN.com/ In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)

Cracking the Code: A Guide to Bioinformatics Job Hunting

Abhi — Mon, 23 Dec 2024 19:36:41 -0600

Entering the world of bioinformatics is an exciting journey, filled with opportunities to combine biology, data science, and technology to address some of the most pressing scientific challenges. However, securing a position in this competitive field can be daunting, especially for newcomers. Here’s a guide to help you navigate the job-hunting process and land your dream role in bioinformatics.

1. Understand the Landscape

Before diving into applications, take the time to understand the bioinformatics job market. Common roles include:

Bioinformatics Analyst/Scientist: Focused on data analysis and interpretation.
Computational Biologist: Combines computational techniques with biological research.
Data Scientist in Genomics: Applies machine learning and statistical models to genomic data.
Software Developer in Bioinformatics: Designs and develops tools and pipelines for biological research.

Familiarize yourself with the key industries hiring bioinformaticians, such as academia, biotech, pharmaceuticals, healthcare, and agriculture.

2. Build a Strong Foundation

Bioinformatics demands a diverse skill set. Ensure you have a solid foundation in the following areas:

Programming Skills: Proficiency in Python, R, or Perl is often required. Familiarity with tools like Bash scripting and version control systems (e.g., Git) is a plus.
Statistics and Data Analysis: Knowledge of statistical methods, machine learning, and data visualization is crucial.
Biological Knowledge: Understanding genomics, transcriptomics, and proteomics will help you communicate effectively with biologists.
Specialized Tools and Databases: Be comfortable using tools like BLAST, Bowtie, and databases like NCBI and Ensembl.

3. Create a Winning Resume and Portfolio

Highlight your technical skills, biological knowledge, and relevant experience. Tips for a standout application:

Tailor your resume to each job, emphasizing skills mentioned in the job description.
Showcase your experience with real-world datasets by linking to your GitHub profile or online portfolio.
Include details of any publications, presentations, or significant projects.

4. Network Actively

Networking is often the key to discovering opportunities. Here’s how to build connections:

Attend Conferences and Workshops: Events like ISMB or specialized bioinformatics workshops are great for meeting professionals.
Engage Online: Join LinkedIn groups, participate in bioinformatics forums, and follow relevant hashtags on Twitter.
Leverage Alumni Networks: Connect with alumni from your university who are working in the field.

5. Gain Relevant Experience

Experience is a major factor for hiring managers. Ways to enhance your profile include:

Internships: Seek out internships in research labs or biotech companies.
Collaborations: Volunteer to work on projects with professors or peers.
Open Source Contributions: Participate in bioinformatics software development on platforms like GitHub.

6. Prepare for Interviews

Bioinformatics interviews often combine technical and behavioral questions. Prepare by:

Reviewing Key Concepts: Refresh your knowledge of algorithms, sequence analysis, and statistical methods.
Practicing Coding: Be ready to solve coding challenges or discuss code snippets.
Understanding the Organization: Research their recent projects, publications, or products.
Preparing Questions: Demonstrate interest by asking about their tools, workflows, or team structure.

7. Stay Resilient and Persistent

Job hunting can be a long process, but persistence pays off. Tips to keep moving forward:

Keep improving your skills by taking online courses or certifications.
Stay updated with advancements in bioinformatics by following journals and blogs.
Apply to multiple positions and don’t get discouraged by rejections. Each application is a learning experience.

Closing Thoughts

Landing a bioinformatics job requires a mix of technical expertise, networking, and resilience. By understanding the market, showcasing your skills effectively, and continuously learning, you’ll be well on your way to a rewarding career in this dynamic field. Remember, the key to cracking the code is perseverance—stay curious, stay determined, and success will follow.

4 positions in high throughput computational metagenomics and systems biology of natural products

Tue, 20 Aug 2013 08:42:29 -0500

The Research and Innovation Centre at the Fondazione Edmund Mach (CRI-FEM) is a major international research institution with strong and expanding research interests in Fruit Genomics, Quality Health and Nutrition of Agricultural Products, Agro-ecosystems Sustainability, Biodiversity and Molecular Ecology.

CRI-FEM hosts GMPF, an International PhD Program in Genomics and Molecular Physiology of Fruit Crops and Fox-Lab, an international initiative in forest and wood research.
4 positions in high throughput computational metagenomics and systems biology of natural products - deadline September 30th, 2013

To support interdisciplinary research, CRI-FEM has established the Computational Biology Centre (CBC).

The mission of CBC is to develop systems-level integrative approaches connecting genotype to phenotype with a special focus on genome-wide analyses and next generation sequencing technologies.

CRI-FEM is seeking to attract 4 high calibre scientists in the areas of high throughput computational metagenomics and systems biology of natural products.

Here below the list of the 4 positions:

http://www.fmach.it/eng/Servizi-Generali/Lavora-con-noi/Annunci-lavoro-e-borse-di-studio/Details-of-the-5-positions-in-high-throughput-computational-metagenomics-and-systems-biology-of-natural-products-deadline-September-30th-2013/Post-doc-in-Metagenomics-screening-and-characterization-of-bioactive-microbial-compounds-130_CRI_MSC

http://www.fmach.it/eng/Servizi-Generali/Lavora-con-noi/Annunci-lavoro-e-borse-di-studio/Details-of-the-5-positions-in-high-throughput-computational-metagenomics-and-systems-biology-of-natural-products-deadline-September-30th-2013/Post-doc-in-Modeling-transcriptional-control-programs-at-a-genome-wide-scale-131_CRI_TCP

http://www.fmach.it/eng/Servizi-Generali/Lavora-con-noi/Annunci-lavoro-e-borse-di-studio/Details-of-the-5-positions-in-high-throughput-computational-metagenomics-and-systems-biology-of-natural-products-deadline-September-30th-2013/Technologist-in-Purification-of-plant-bioactive-molecules-from-complex-matrixes-132_CRI_PBM

http://www.fmach.it/eng/Servizi-Generali/Lavora-con-noi/Annunci-lavoro-e-borse-di-studio/Details-of-the-5-positions-in-high-throughput-computational-metagenomics-and-systems-biology-of-natural-products-deadline-September-30th-2013/Researcher-in-Methods-for-algorithmic-and-integrative-genomics-for-metagenomics-134_CRI_AIG

For more information on the CBC or informal inquiries on the advertised positions please contact Dr Duccio Cavalieri (e-mail duccio.cavalieri@fmach.it).

A Bioinformatician’s Lament

LEGE — Thu, 29 May 2025 01:33:31 -0500

"I have a presentation tomorrow," they say,

With hopeful eyes, like it’s all child's play.
As if results bloom overnight, full-grown—
Not wrangled from chaos, and error-prone.

Oh brave soul, sit, let’s walk through the tale,
Of pipelines broken and servers that fail.
The journey starts: “The data? It’s there—
Just fetch it from S3, easy, I swear.”

Now I summon awscli with dread,
Reset my keys, credentials fed.
Configure regions, IAM roles too—
All this, and still no peek at the view.

Next up, the tool: “It’s open source!”
On GitHub, rotting, no sign of remorse.
Python 2.7, some GCC trick—
The install alone might make you sick.

Finally, progress! The pipeline runs…
Till RAM collapses and error stuns.
Oh, and the metadata? A crime,
Merged cells, font soup, out of time.

Sample IDs—what a cryptic game:
Sample_1, S1, sample-1... the same?
Controls mislabeled, cases flipped,
No wonder my sanity's starting to slip.

Then QC plots, PCA joy—
Wait, that’s a tumor labeled as a boy?
Clusters cross, and axes lie,
And I still don’t know which sample’s "guy."

But the clock ticks on, and it’s half-past doom,
They want the final UMAP soon.
With pastel colors, labeled clear—
"Can we move that legend to right here?"

Tweak by tweak, I adjust each frame,
Resize Panel B, annotate a name.
Export the plot—it starts to gleam…
Then my laptop crashes. I scream.

This is the grind, the long-haul game,
Where science hides behind code and flame.
No “Export to Nature” button to press,
Just toil and logic and hope for success.

So next time you whisper that fated line—
“I have a talk, can you make it shine?”
Know: bioinformatics is craft, not a click,
It’s science with scars, not just a quick fix.

To all who debug at 3AM light,
Who ghostwrite figures through sleepless night—
You are the backbone, silent and true,
First-author-worthy, if only they knew.

"कल मेरी प्रेज़ेंटेशन है," वो कहते हैं,

आशा भरी आँखों से, जैसे सब सहज है।
जैसे परिणाम रातोंरात प्रकट हो जाएं—
ना कि डेटा की भूलभुलैया से उखाड़े जाएं।

आओ बैठो, एक किस्सा सुनाता हूँ,
जहाँ पाइपलाइन टूटती है, और सर्वर भी थक जाते हैं।
कहानी शुरू होती है: “डेटा तो है—
बस S3 बकेट में, एकदम पास में कहीं।”

अब awscli बुलाता हूँ डरते हुए,
कुंजी सेट करूँ, क्रेडेंशियल जोड़ूं, रीजन भरूँ।
इतनी मशक्कत, फिर भी डेटा नहीं मिला,
बस सेटअप में ही पूरा दिन चला।

फिर आता है टूल: “ओपन-सोर्स है!”
GitHub पर है, 2019 से सूखा पड़ा है।
Python 2.7 चाहिए, एक पुराना कम्पाइलर,
और साथ में थोड़ी सी दुआ की ताकत।

आख़िरकार टूल चला, खुशी सी हुई,
लेकिन रन करते ही, मेमोरी ने हार मानी।
और मेटाडेटा? एक एक्सेल की आफ़त,
मर्ज़ किए हुए सेल, बस और क्या चाहिए काफ़ियत?

सैंपल आईडी? बस भगवान ही जाने—
Sample_1, sample-1, S1, और control1—
ये सब एक ही सैंपल हैं क्या?
पता तब चलता है जब पूछो दो-तीन बार।

काउंट मैट्रिक्स तैयार, अब R या Python की बारी,
QC करो, PCA प्लॉट—पर कुछ गड़बड़ भारी।
ट्यूमर और नॉर्मल का अदला-बदली खेल,
बार-बार, वही पुरानी झमेल।

आख़िर में आया मॉडलिंग का समय,
स्टैट्स, प्लॉट्स, डिफरेंशियल एक्सप्रेशन का श्रम।
लेकिन घड़ी में 5 बज चुके हैं जनाब,
और 8 बजे तक UMAP चाहिए, साफ़-सुथरा जबाब।

तो मैं कोड लिखता हूँ रात भर बैठ कर,
कलर पैलेट, जीन लेबल, लीजेंड बाहर रख कर।
फ़ॉन्ट, पैनल, एक्सिस सब सुधार,
एक्सपोर्ट करता हूँ... और लैपटॉप कहता है—"अब नहीं यार!"

इसीलिए बायोइन्फॉर्मेटिक्स में लगता है समय,
ये “बस सीरत चलाओ” या “वोल्कैनो प्लॉट बनाओ” नहीं है।
ये है सिस्टम एडमिन का काम, डेटा की सफ़ाई,
QC, डिबगिंग, और सांइस की सच्ची लड़ाई।

तो कुछ सीखें इस व्यथा से आप भी आज:
24 घंटे पहले चमत्कार मत माँगिए।
अच्छे फ़िगर साफ़ डेटा से बनते हैं।
बायोइन्फॉर्मेटिक्स जादू नहीं, विज्ञान है।
समय से बात कीजिए, प्रक्रिया का सम्मान कीजिए।

और उन सभी बायोइन्फॉर्मेटिशियनों को सलाम,
जो दूसरों की प्रेज़ेंटेशन के लिए रातों में जागते हैं—
तुम हो फ़िगर्स के भूत लेखक,
तुम हो बिना नाम के सह-लेखक।
तुम पहले लेखक बनने के हक़दार हो—
और एक लंबी नींद के भी।

Note: Written with the help of AI/LLM Tools !

Dynamic Programming Alignment

Thu, 22 Aug 2013 09:38:28 -0500

lecture 9, Chem. C100, Spring 2013, UCLA

Courses to Get You Started with Bioinformatics

LEGE — Tue, 30 Sep 2025 13:07:19 -0500

Bioinformatics is now at the heart of modern biology and medicine. From decoding genomes and predicting antimicrobial resistance, to developing personalized medicine and advancing evolutionary research, computational skills are no longer optional — they are essential.

Yet, for many students, biologists, and even computer scientists, the question is: “Where do I begin?” With so many platforms, books, and tutorials available, it’s easy to feel overwhelmed.

To make it easier, I’ve compiled 10 excellent resources — ranging from beginner-friendly introductions to advanced computational genomics courses. Many of these are freely available, created by pioneers in the field, and widely used in classrooms and research labs worldwide.

Whether you are a complete beginner or looking to strengthen your foundations, these courses will help you build the skills needed to analyze biological data, design workflows, and think computationally about complex biological systems.

1. HarvardX Data Analysis for Genomics by Rafael Irizarry

From the almighty Rafa, this set of online courses (via edX/HarvardX) is a classic starting point for genomic data science and bioinformatics.

2. Applied Computational Genomics – Aaron Quinlan

Aaron Quinlan (creator of bedtools and many other tools) has made his course materials open. A practical, tool-driven genomics introduction.

3. Bioinformatics Algorithms (Coursera + Companion Book)

Find the highly visual video classes on Coursera, backed by the popular Bioinformatics Algorithms book.

4. The Biostar Handbook

Not a course per se, but a hands-on manual by Istvan (founder of Biostars.org) that’s even used in classes at Penn State.

5. Introduction to Bioinformatics and Computational Biology (by Shirley Liu)

A comprehensive introduction from Shirley Liu’s lab (Harvard DFCI). Covers both theory and computational practice.

6. Data Carpentry: Genomics Workshops

Community-driven training workshops that focus on practical, reproducible research. I was honored to serve as curriculum committee chair here.

7. Computational Genomics: Applied Comparative Genomics

From the Schatz Lab — applied comparative genomics with real-world data.

8. Introduction to Computational Biology (Mike Love, creator of DESeq2)

This course bridges statistics, biology, and computation — a solid primer for anyone entering computational biology.

9. MIT Computational Biology (6.047 / 6.878 / HST.507) by Manolis Kellis

Covers genomes, networks, evolution, and health. A deep-dive from MIT’s OpenCourseWare archive.

10. An Introduction to Applied Bioinformatics

An interactive textbook with Python code, designed for practical applied bioinformatics learning.

PhD position in biochemistry towards bioinformatics at the Department of Biochemistry and Biophysics.

Tue, 03 Sep 2013 06:09:03 -0500

PhD position in biochemistry towards bioinformatics at the Department of Biochemistry and Biophysics. Reference number: SU FV-2293-13. Deadline for application: September 10, 2013.

Project title: Functional Inference from Domain Architecture and Orthology

Requirements

To be accepted as a PhD student, credits corresponding to four years of full-time studies at the undergraduate level are required, including credits corresponding to at least two years of fulltime studies in chemistry, life sciences or physics, depending on the program. The credits should include courses at the advanced level (second cycle) corresponding to one year and of these one semester should be a degree thesis. In order to facilitate the evaluation of merits and suitability for the PhD studies the curriculum vitae (CV) should contain information about the extent and focus of the academic studies. The quantity (as part of an academic year) and the quality mark of courses in chemistry and physics are of particular interest. The title, number of credits and the length in full-time months of undergraduate thesis and project work, should be specified.

Information

More information about the project can be provided by the project leader. General information about the PhD training program may be requested from the director of graduate studies, Stefan Nordlund, stefan@dbb.su.se or from Lena Mäler, Head of Department (prefekt), lenam@dbb.su.se

Further information on the web:

The Department of Biochemistry and Biophysics: www.dbb.su.se

Stockholm University: www.su.se/english

Faculty of Science: www.science.su.se/english

The handbook for postgraduate students: www.doktorandhandboken.nu/english

Application The application should contain a personal letter (a letter of intent explaining why you are interested in the specific project, why you are interested in studying for a PhD, what you hope to accomplish during your PhD studies, and what skills you can bring to this project), a curriculum vitae, a list of two persons who may act as referees (with telephone numbers and e-mail addresses), copies of degree certificates and transcripts of academic records, and a copy of your undergraduate thesis and articles, if any.

In order to apply for this position, please use the Stockholm University web-based application form (where it is possible to select language):

To the application form for this position.

Welcome with your application no later than September 10, 2013.

Project leader: Erik Sonnhammer, Erik.Sonnhammer@sbc.su.se,
www.sonnhammer.sbc.su.se

Advertisement: http://www.su.se/english/about/vacancies/phd-studies/phd-position-in-biochemistry-towards-bioinformatics-1.143446

Senior Bioinformatics Programmer and SRF at BIOTECH PARK Lucknow

Fri, 23 Aug 2013 04:55:51 -0500

BIOTECH PARK

Advt. No. 3 (8)/BP/13

A walk-in-interview will be held in the Biotech Park Office at Sector G, Jankipuram, Kursi Road, Lucknow (U.P.) August 27, 2013 at 11.00 a.m. for the following posts of DBT sponsored project tenable at Biotech Park. Interested candidates fulfilling the requisite qualifications, experience and age as given below, may appear on the date of interview, before the Selection Committee. The candidate will have to join immediately.

INTERVIEW ON August 27, 2013 at 11.00 A.M.

2. SENIOR PROGRAMMER (ONE POST)

a) Educational Qualification M.Sc. Bioinformatics with minimum 60% marks with two years of relevant experience or B.Tech. Bioinformatics or Biotechnology with minimum 60% marks with two years experience in Bioinformatics.

b) Job Requirement Development of databases in multi user environment and application softwares, maintenance of website, Drug designing and QSAR study etc.

c) Desirable Knowledge of Bioinformatics tools, Windows, Linux, C++, JAVA / JAVA Script, Visual Basic, CGI, DBMS/RDBMS and HTML. Experience in various domains of bioinformatics such as structure based drug designing, Newtonian dynamics and OSAR studies.

d) Age Below 35 years (as on the date of interview)

e) Emoluments Rs. 12,000/- per month fixed.

Appointment will be made initially for one year extendable on satisfactory performance till the duration of the project.

3. SENIOR RESEARCH FELLOW: (ONE POST)

a) Educational Qualification M.Sc. in Biotechnology/Botany with minimum 60% marks and knowledge of handling database & database searching.

b) Essential Qualification Expertise in windows, Microsoft excel.

c) Desirable Good knowledge of statistical software packages like SPSS.

d) Age Below 35 years ( as on the date of interview)

e) Job Requirement: Management of database & website in multi user environment, computation of biological field data and generation of reports.

f) Emoluments

18000+ HRA for Net/GATE qualified
14000+ HRA for others

The appointment will be made till the duration of project.

Note: All the candidates should report for interview on or before 10.45 A.M.

General Conditions

The aforesaid positions are purely temporary and do not give the incumbent any right whatsoever for appointment on regular basis.
More Advertisement: http://www.biotechpark.org.in/html/jobs%20in%20Biotech%20Park/Job_2013_04.htm

Great Place to Study Bioinformatics in Europe

Rahul Agarwal — Sun, 18 Aug 2013 18:41:34 -0500

Study bioinformatics is like being jack of all trade so it is important you choose where it will be good backup of computer science, and natural science infrastructure and faculty. Especially having a good teachers in computer science is indispensible.

Few places in Europe where good (and @some places no tution fees) master bioinformatics courses and recommended are:

KU Leuven, Belgium

http://onderwijsaanbod.kuleuven.be/opleidingen/e/CQ_50269018.htm

ETH, Zurich

http://www.cbb.ethz.ch/

University of Copenhagen, Denmark

http://studies.ku.dk/masters/bioinformatics/

University of Helsinki, Finland

http://www.cs.helsinki.fi/en/mbi/

Stockholm University, Sweden

http://www.sbc.su.se/masters/

Universities in Netherlands