Model Curriculum...• Explain the basic concepts of bioinformatics, computational biology, biological databases, data analysis, machine learning and algorithm , development and implementation

Bioinformatics Associate/ Analyst

Model Curriculum

Bioinformatics Associate/ Analyst SECTOR:

SUB-SECTOR: OCCUPATION:

REF ID: NSQF LEVEL:

LIFE SCIENCES CONTRACT RESEARCH BIOINFORMATICS LFS/Q3902, V1.0 4


Complying to National Occupational Standards of Job Role/ Qualification Pack: ‘Bioinformatics Associate/ Analyst’ QP No. ‘LFS/ Q3902,V1.0

NSQF Level 4’

Date of Issuance: Aug 16th , 2019

Valid up to: Aug 01st

, 2023

* Valid up to the next review date of the Qualification Pack

Authorized Signatory (Life Sciences Sector Skill Development Council)


TABLE OF CONTENTS

1. Curriculum 01 2. Trainer Prerequisites 08 3. Assessment Criteria 09

Bioinformatics Associate/ Analyst 1

Bioinformatics Associate/ Analyst CURRICULUM / SYLLABUS This program is aimed at training candidates for the job of a “Bioinformatics Associate/ Analyst”, in the “Life Sciences” Sector/Industry and aims at building the following key competencies amongst the learner

Program Name Bioinformatics Associate/ Analyst

Qualification Pack Name & Reference ID. ID Bioinformatics Associate/ Analyst LFS/Q3902, V1.0

Version No. 1.0 Version Update Date 16-08-2019

Pre-requisites to Training

Graduate in Science subjects/ Bioinformatics/ Biotechnology or Graduate Engineer in Biotechnology/ Bioinformatics/Biomedical Engineering/ Computational Science

Training Outcomes After completing this program, participants will be able to: • Outline industry ecosystem, regulations and ethical practice to enable

him/herself for establishing the industry standards in his/her performance by practicing project management/ proposal development skills.

• Explain the basic concepts of bioinformatics, computational biology, biological databases, data analysis, machine learning, and algorithm development and implementation.

• Perform data mining and data transformation by using statistical tools and various programming scripts.

• Report and organize the results of data analysis in prescribed templates and formats.

• Ensure compliance to meet work requirements by using appropriate resources correctly and efficiently.

• Coordinate with the manager, team members, and cross-functional teams to meet functional goals.


This course encompasses 5 out of 5 National Occupational Standards (NOS) of “Bioinformatics Associate/ Analyst” Qualification Pack issued by “Life Sciences Sector Skill Development Council”. Sr. No. Module Key Learning Outcomes Equipment Required

1 Orientation for Bioinformatics Occupation Theory Duration (hh:mm) 05:00 Practical Duration (hh:mm) 00:00 Corresponding NOS Code Bridge Module

• Explain the life sciences industry and bioinformatics occupation

• Explain the organizational structure and employment benefits in the life sciences Industry

• Explain the regulatory framework, rules, and regulations applicable for bioinformatics in the life sciences Industry

• Explain the role of a Bioinformatics Associate/ Analyst and required skills and knowledge (as per Qualification Pack) and its career path

Computer, LCD Projector & Screen/ LCD Monitor, Mic, Sound System, Laser Pointer, White/ Black Board, White Board Marker/ chalk, duster, flip charts

2 Fundamental concepts of Bioinformatics Theory Duration (hh:mm) 05:00 Practical Duration (hh:mm) 12:00 Corresponding NOS Code Bridge Module

• Explain the basic concepts of bioinformatics

• Illustrate the key concepts of techniques used in genomics, transcriptomics, and proteomics

• Establish the modalities of proteomic studies that are applied in the latest research in life sciences

• Explain the concepts of dynamic protein biology and create processes of application to translate across biological systems

• Identify molecular markers and concepts of transcriptomics

• Recall the basics of whole genome sequencing techniques and annotations.

Computer, LCD Projector & Screen/ LCD Monitor, Mic, Sound System, Laser Pointer, White/ Black Board, White Board Marker/ chalk, duster, flip charts

3 Introduction to Programming Scripts Theory Duration (hh:mm) 40:00 Practical Duration (hh:mm) 64:00 Corresponding NOS Code LFS/N3902

• Explain the basic techniques used to create scripts for automating system administration tasks

• Explain the use of scripting in developing applications using networking and databases

• Demonstrate the use of programming scripts to develop or customize prototype applications

• Use the programming script to test various customized programming applications.

• Demonstrate the use of pattern matching with regular expressions in processing text

Computer system, LCD Projector & Screen/ LCD Monitor, Headphone with Mic, Sound System, Laser Pointer, White/ Black Board, White Board Marker/ chalk, duster, flip charts Development Software: Linux OS, Python/Perl/ R and C++/Java

4 Machine Learning and Image Analysis

• Recall basics for machine learning for building new adaptive intelligent systems

Computer system, LCD Projector & Screen/ LCD


Sr. No. Module Key Learning Outcomes Equipment Required

Theory Duration (hh:mm) 50:00 Practical Duration (hh:mm) 64:00 Corresponding NOS Code LFS/N3902

and powerful predictive models for intelligent data analysis

• Explain linear models and nearest-neighbours (learning algorithms and properties, regularization).

• Recall basics of probabilistic ML and computer vision

• Implement models for support vector machines, Kernel SVM, Naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-means clustering and more in Python

• Validate machine learning models and decode various accuracy metrics

• Practice boosting and bagging techniques • Comprehend theoretical concepts and

how they relate to the practical aspects of machine learning for image analysis

Monitor, Headphone with mic, Sound System, Laser Pointer, White/ Black Board, White Board Marker/ chalk, duster, flip charts, Big Data Analysis Server:10MB Cache, 2.5GHz processor, 1 TB RAM, 28 TB storage, 8 Cores, 398 Gigaflops MPI Interconnect: 36 port InfiniBand QDR switch Network Interconnect: 48 port Gigabit Ethernet with 4*10G ports Storage Interconnect: 10G Ethernet via GigE switch Tape Library: 45 TB (1.5*30) storage capacity PFS Storage: 60 TB (upgraded with 180 TB and additional 89.32 TB added to overall 330 TB Storage)

5 Statistical Methods and Tools for data extraction and preparation Theory Duration (hh:mm) 40:00 Practical Duration (hh:mm) 64:00 Corresponding NOS Code LFS/N3902

• Explain data characteristics and distribution of data structure

• Explain the basic concepts of descriptive statistics, correlation, and regression, probability & Bayes theorem, sampling, distribution and hypothesis theorem

• Describe the exact methods of data analysis for the problem under investigation

• Practice various statistical tools to manage data, run analyses and produce data visualizations

• Apply the descriptive statistics methods for quantitative reasoning and data visualization

• Apply the basics of inferential statistics for making valid generalizations from sample data

• Interpret statistical outputs to inform work-oriented decisions

Computer system, LCD Projector & Screen/ LCD Monitor, Headphone with mic, Sound System, Laser Pointer, White/ Black Board, White Board Marker/ chalk, duster, flip charts, SPSS, R Studio

6 Data Mining Theory Duration (hh:mm) 30:00 Practical Duration (hh:mm) 64:00 Corresponding NOS Code LFS/N3902

• Perform data mining from a large source of data

• Acquire data warehouse basics, its life cycle and implementation

• Demonstrate the skills to classify and cluster data using outlier analysis

• Describe different forecasting techniques • Plan for the data import from different

databases • Describe the concept of Hadoop and R

language • Describe the data analytics project life

cycle

Computer system, LCD Projector & Screen/ LCD Monitor, Mic, Sound System, Laser Pointer, White/ Black Board, White Board Marker/ chalk, duster, flip charts, Data mining tools: RapidMiner, Hadoop and Spark



7 Basics of Algorithm Development and implementation Theory Duration (hh:mm) 30:00 Practical Duration (hh:mm) 56:00 Corresponding NOS Code LFS/N3901

• Explain various methods of program design

• Describe the basic structures (flow and data) for algorithm development

• Distinguish between the pros and cons of efficient and naïve algorithms

• Explain structured programming rules • Apply logical and algorithmic thinking

while programming • Apply greedy algorithms to different cases • Use the divide and conquer technique to

solve problems involving large databases • Make use of object-oriented approaches

in algorithm development and implementation

• Define algorithm based on structured language

• Use algorithm in the collective data processing

• Refine and implement a well-structured algorithm for data processing and analysis

• Verify correctness of algorithms

Computer system, LCD Projector & Screen/ LCD Monitor, Headphone with Mic, Sound System, Laser Pointer, White/ Black Board, White Board Marker/ chalk, duster, flip charts, Development Software: Python, R, C++, Java

8 Introduction to Computational Biology Theory Duration (hh:mm) 30:00 Practical Duration (hh:mm) 64:00 Corresponding NOS Code LFS/N3901

• Explain the concept of computational biology and bioinformatics

• Describe the concepts and applications of pathways, principles of Next Generation Sequencing (NGS), omics and Clinical Trial

• Explain the types of biological data and biomedical data

• Explain the statistical methods developed and widely applied in several branches of computational biology, such as gene expression, sequence alignment, motif discovery, comparative genomics, and biological networks

• Discuss the basic statistical concepts and use of statistical inference to solve biological problems

• Explain the beginnings of molecular computing Adelman’s Experiment

• Discuss the basic principles of microarray and molecular techniques

• Explain molecular phylogeny and the basic concepts of phylogenetics

• Describe the tools used for phylogenetic analysis

• Identify biological samples • Make use of sequence analysis and

perform sequence alignment using algorithms

Computer system, LCD Projector & Screen/ LCD Monitor, Mic, Sound System, Laser Pointer, White/ Black Board, White Board Marker/ chalk, duster, flip charts, 16 TB 4-way storage Server: 96 GB RAM, 8TB storage, 4 Cores, 80 Giga Flops Data Analysis Server:10MB Cache, 2.5GHz processor, 1 TB RAM, 28 TB storage, 8 Cores, 398 Gigaflops MPI Interconnect: 36 port InfiniBand QDR switch Network Interconnect: 48 port Gigabit Ethernet with 4*10G ports Storage Interconnect: 10G Ethernet via GigE switch Tape Library: 45 TB (1.5*30) storage capacity PFS Storage: 60 TB (upgraded with 180 TB and additional 89.32 TB added to overall 330 TB Storage) Development Software: Python, R, C++, Java, Development Libraries or Platforms: OpenCV, TensorFlow, Theano, Knime, Scikit-learn, Torch, Keras



9 Introduction to Biological Databases Theory Duration (hh:mm) 30:00 Practical Duration (hh:mm) 56:00 Corresponding NOS Code LFS/N3901

• Recall the biological and medical terminology used in omics projects

• Explain molecular phylogeny, concepts of phylogenetics and tools for phylogenetic analysis

• Explain the biological databases and their classification

• Describe bioinformatics database search engines

• Identify biological samples, genome browsers, and bioinformatics database search engines

• Identify visualization tools and other tools used in computational biology

Computer system, LCD Projector & Screen/ LCD Monitor, Mic, Sound System, Laser Pointer, White/ Black Board, White Board Marker/ chalk, duster, flip charts Big Data Analysis Server:10MB Cache, 2.5GHz processor, 1 TB RAM, 28 TB storage, 8 Cores, 398 Gigaflops MPI Interconnect: 36 port InfiniBand QDR switch Network Interconnect: 48 port Gigabit Ethernet with 4*10G ports Storage Interconnect: 10G Ethernet via GigE switch Tape Library: 45 TB (1.5*30) storage capacity PFS Storage: 60 TB (upgraded with 180 TB and additional 89.32 TB added to overall 330 TB Storage)

10 Biological Data Analysis Theory Duration (hh:mm) 30:00 Practical Duration (hh:mm) 56:00 Corresponding NOS Code LFS/N3901

• Perform structure predictions and analysis

• Analyse biological data, produce and interpret the predictions of the software

• Perform sequence analysis and predictions of nucleic sequence and protein sequence

• Explain the Institute of Electrical and Electronics Engineers (IEEE) standards applicable for bioinformatics analysis

• Perform integrative analysis of omics big data

Computer system, LCD Projector & Screen/ LCD Monitor, Mic, Sound System, Laser Pointer, White/ Black Board, White Board Marker/ chalk, duster, flip charts Big Data Analysis Server:10MB Cache, 2.5GHz processor, 1 TB RAM, 28 TB storage, 8 Cores, 398 Gigaflops MPI Interconnect: 36 port InfiniBand QDR switch Network Interconnect: 48 port Gigabit Ethernet with 4*10G ports Storage Interconnect: 10G Ethernet via GigE switch Tape Library: 45 TB (1.5*30) storage capacity PFS Storage: 60 TB (upgraded with 180 TB and additional 89.32 TB added to overall 330 TB Storage)

11 Data Delivery and Reporting Theory Duration (hh:mm) 50:00

• Correlate data analysis and analysed results

• Perform data validation and update data on the database

• Follow technical writing rules and method to write the report

Computer system, LCD Projector & Screen/ LCD Monitor, Mic, Sound System, Laser Pointer, White/ Black Board, White Board Marker/ chalk, duster, flip charts, MPI



Practical Duration (hh:mm) 80:00 Corresponding NOS Code LFS/N3903

• Recall templates and practice formats used for sharing and storing data/information

• Evaluate the resulting outcome according to end user requirement

• Ensure that the user requirements are met for data visualization in consultation with seniors

• Organize and report the results of the analysis to seniors within given timelines

• Carry out reporting of inaccurate data/information

Interconnect: 36 port InfiniBand QDR switch Network Interconnect: 48 port Gigabit Ethernet with 4*10G ports Storage Interconnect: 10G Ethernet via GigE switch Tape Library: 45 TB (1.5*30) storage capacity

12 Work Management Theory Duration (hh:mm) 10:00 Practical Duration (hh:mm) 30:00 Corresponding NOS Code SSC/N9001

• Define the scope of work and working within limits of authority

• Summarize the details of the work and work environment

• Explain the importance of maintaining confidentiality

• Recall organization’s policies and procedures

• Explain the process of escalation of query, request, complaint and problem resolution

Computer system, LCD Projector & Screen/ LCD Monitor, Mic, Sound System, Laser Pointer, White/ Black Board, White Board Marker/ chalk, duster, flip charts

13 Coordinate with Supervisor and cross-functional teams Theory Duration (hh:mm) 10:00 Practical Duration (hh:mm) 30:00 Corresponding NOS Code LFS/N0107

• Follow the instructions of the manager to understand the work output requirements

• Perform the daily tasks assigned by the manager

• Report any challenges in the project to the manager

• Coordinate with team members and cross-functional teams for technical support

• Explain the process of escalation of query, request, complaint and problem resolution

Computer system, LCD Projector & Screen/ LCD Monitor, Mic, Sound System, Laser Pointer, White/ Black Board, White Board Marker/ chalk, duster, flip charts

Total Duration Theory Duration 340:00 Practical Duration 660:00

Unique Equipment Required: Computer Lab, Computer system, LCD Projector & Screen/ LCD Monitor, Headphones with Mic, Sound System, Laser Pointer, White/ Black Board, White Board Marker/ chalk, duster, flip charts, Big Data Analysis Server:2.5GHz processor, 1 TB RAM, 28 TB storage, 8 Cores, 398 Gigaflops MPI Interconnect: 36 port InfiniBand QDR switch, Network Interconnect: 48 port Gigabit Ethernet with 4*10G ports, Storage Interconnect: 10G Ethernet via GigE switch, Tape Library: 45 TB (1.5*30) storage capacity, PFS Storage: 60 TB (upgraded with 180 TB and additional 89.32 TB added to overall 330 TB Storage), Data mining tools: RapidMiner, Development Software: Python, R,



C++, Java, Development Libraries or Platforms: OpenCV, TensorFlow, Theano, Knime, Scikit-learn, Torch, Keras, SPSS, R Studio

Grand Total Course Duration: 1000 hours 00 minutes (200 hours of OJT is recommended) (This syllabus/ curriculum has been approved by Life Sciences Sector Skill Development Council)


Trainer Prerequisites for Job role: “Bioinformatics Associate/ Analyst” mapped to Qualification Pack: “LFS/ Q3902, V1.0”

Sr. No. Area Details 1 Description To deliver accredited training service, mapping to the curriculum detailed above,

in accordance with the Qualification Pack “LFS/Q3902, V1.0”. 2 Personal

Attributes Aptitude for conducting training, and pre/ post work to ensure competent, employable candidates at the end of the training. Strong communication skills, interpersonal skills, ability to work as part of a team; a passion for quality and for developing others; well-organized and focused, eager to learn and keep oneself updated with the latest in the mentioned field.

3 Minimum Educational Qualifications

B. Tech Biotechnology/ B. Tech Computer Science/ M. Sc Biotechnology/ Biology/Masters in any science disciplinary

4a Domain Certification

Certified for Job Role: “Bioinformatics Associate/ Analyst” mapped to QP: “LFS/Q3902, V1.0”. The minimum accepted score is 80% as per LSSSDC guidelines.

4b Platform Certification

Recommended that the trainer is certified for the job role: “Trainer”, mapped to the Qualification Pack: “MEP/Q02601”. The minimum accepted score is 80% as per LSSSDC guidelines.

5 Experience Minimum Six (6) years’ experience in Bioinformatics/ Computational Biology for non-trained and non-qualified talent with B. tech Biotechnology/ B. Tech Computer Science/ M.Sc. Biotechnology/ Biology/any other science disciplinary field education qualification Or Minimum Four (4) years’ experience in life Bioinformatics/ Computational Biology for non-trained and non-qualified talent with M. tech Biotechnology/ M. tech Computer Science/ any other science disciplinary education qualification


Annexure: Assessment Criteria Please refer to the QP PDF for the Assessment Criteria.

Documents

Model Curriculum...• Explain the basic concepts of bioinformatics, computational biology, biological databases, data analysis, machine learning and algorithm , development and implementation