Muthukumarasamy Karthikeyan ,
Ph.D.,
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|
1. |
Name and full correspondence address |
Dr. Muthukumarasamy
Karthikeyan Chief Scientist Chemical Engineering and Process Development CSIR-National Chemical Laboratory, Pune |
|
2. |
Email(s) and contact number(s) |
m.karthikeyan@ncl.res.in, karthincl@gmail.com Lab no.+91-(0)20-25902483 |
|
3. |
Institution |
CSIR-National Chemical Laboratory |
|
4. |
Date
of Birth |
7th
December 1968 |
|
5. |
Gender
(M/F/T) |
M |
Academic Qualification:
|
Sl.No |
Degree |
Year |
Subject |
University/Institute |
|
|
B.Sc |
|
|
Tagore
Arts College Pondicherry
University |
|
|
M.Sc |
|
MSc
Chemistry |
CPGS
Pondicherry University |
|
3 |
Ph.D |
1998 |
Organic
Chemistry |
Pune
University (NCL Pune) |
|
4 |
BOYSCAST
Fellow (DST) |
|
Chemoinformatics |
University
of Northcarolina, Chapel Hill, NC, USA |
|
5 |
DBT
Overseas Associate |
|
Chemoinformatics |
University
of Northcarolina, Chapel Hill, NC, USA |
Ph.D thesis title, Guide’s Name, Institute/Organization/University,
Year of Award Title: Photoinduced Electron Transfer (PET) promoted carboannulation Strategy: Arene
Radical Cation in carbon-carbon bond formation reaction.". Guide Name: Dr Ganesh Pandey, Institute:
CSIR- National Chemical Laboratory , Pune (Degree
awarded by Pune University in 2008).
Work experience (in
chronological order).
|
Sl.No |
Positions held |
Name of the Institute |
From
|
To |
|
1 |
Scientist B |
DRDO-ARDE Pune |
18-Mar-1998 |
12-Mar-2000 |
|
2 |
Scientist C (Scientist) |
CSIR-NCL, Pune |
13-Apr-2000 |
12-Mar-2005 |
|
3 |
Scientist E1 (Senior Scientist) |
CSIR-NCL, Pune |
13-Apr-2005 |
12-Mar-2010 |
|
4 |
Scientist E2 (Pr. Scientist) |
CSIR-NCL, Pune |
13-Apr-2010 |
12-Mar-2016 |
|
5 |
Scientist F (Sr
Pr Scientist) |
CSIR-NCL, Pune |
13-Apr-2016 |
12-Mar-2021 |
|
6 |
Scientist G / Chief Scientist |
CSIR-NCL, Pune |
13th April 2021 |
Till date |
Areas of research:
His
Research Experience includes Synthetic Organic Chemistry: Multi-step organic
synthesis, Carboannulation, Spiro cyclization, chemoinformatics, bioinformatics, artificial intelligence,
robotics, Internet of chemical things etc.
Awards:
He
is a recipient of several recognitions starting with Commendation Certificate by Defence
Research and Development Organization (DRDO), New Delhi, 26 Jan 1999 and DST BOYSCAST Award (2003-04) for
post-doctoral research in University of Northcarolina,
Chapel hill in the area of ML, QSAR for anticancer drug design. He is also the
recipient of DBT Overseas Associate
Award (2007-08) to perform research in UNC-CH, USA. He is the winner of Innocentive global award for the year 2017 and WAZOKU
global award for the year 2023 for solving problems related to multidimensional
data analysis.
Others:
He has published
over 30 publications in international Journals of repute and has 12 patents to
his credit. Over 15 M.Sc / BTech students have
finished their dissertation works, 2 students have been awarded Ph.D and presently 1 student are working for his Ph.D programme. Has 613 citations with 13
as h-index and 19 as i10 index (from google scholar).
Research publications (Google Scholar)
1]
S Kothari, S Sharma, S Shejwal, A Kazi,
M D'Silva, M Karthikeyan An
explainable AI-assisted web application in cancer drug value prediction 2024 MethodsX, 102696
2]
N Shaikh, RK Linthoi, KV Swamy,
M Karthikeyan, R Vyas Comprehensive molecular docking and dynamic simulations
for drug repurposing of clinical drugs against multiple cancer kinase targets
2023 Journal of Biomolecular Structure and Dynamics
41 (16), 7735-7743
3]
N Shaikh, S Bapat, M Karthikeyan, R Vyas Machine
Learning Approaches for Identification of Potential Biomarkers from Cancer
Omics Data 2023 Web Scraping for Ovarian Cancer Detection: Utilizing
Open-Source Whisper AI for Identifying Relevant Terminology and Improving Early
Diagnosis
4]
V Khedkar, P Bagane, S
Kothari, A Gupta, U Singh, S Gupta, T Agrawal,M Karthikeyan, Cancer XAI: A Responsible
Model for Explaining Cancer Drug Prediction Models 2023 International Journal
of Intelligent Systems and Applications in Engineering …
5]
S Kothari, RR Patil, S Sharma, A, M Karthikeyan,Kazi, M D'Silva, S Shejwal, ...
Fine-tuning ASR Model Performance on Indian Regional Accents for Accurate
Chemical Term Prediction in Audio 2023 International Journal of Intelligent
Systems and Applications in Engineering …
6]
S Kothari, S Chiwhane,M Karthikeyan, R Satya, MA Ansari, S Mehta, P
Naranatt, ... Method for harvesting 3D chemical
structures from file formats 2023 International Journal of Intelligent Systems
and Applications in Engineering …
7]
M Karthikeyan, R Vyas BESFA: bioinformatics based evolutionary, structural
& functional analysis of Prostate, Placenta, Ovary, Testis, and Embryo
(POTE) paralogs 2022 US Patent 11,456,061
8]
S Qazi, BP Jit, A Das, M
Karthikeyan, A Saxena, MD Ray, AR Singh, ... A Review
on Computational Analysis of Big Data in Breast Cancer for Predicting Potential
Biomarkers 2022 Heliyon 8 (9)
9]
N Shaikh, S Bapat, M Karthikeyan, R Vyas Generalized
NRTL model for predicting vapor-liquid equilibrium data from activity
coefficient of binary component systems: using molecular descriptors 2022
Current topics in medicinal chemistry 22 (21), 1793-1810
10]
A Behhara, DSR Badrinarayanan,
I Rahman, M Karthikeyan Bibliometric analysis of named entity recognition for chemoinformatics and biomedical information extraction of
ovarian cancer 2022 ACMS 2022, April 14-16, 2022, IIChE,
Kolkata
11]
V Khedkar, C Fernandes, D
Desai, M Karthikeyan,R Mansi, G Chavan, SK Tidke,
... Design of novel drug-like molecules using informatics rich secondary
metabolites analysis of Indian medicinal and aromatic plants 2021 Lincoln:
Library Philosophy and Practice, University of Nebraska, 1-10
12]
D Karade, D Vijayasarathi,
N Kadoo, R Vyas, PK Ingle, M Karthikeyan Remote monitoring and controlling
physical parameters of a material under transportation 2020 Combinatorial
Chemistry & High Throughput Screening 23 (10), 1113-1131
13]
M Karthikeyan, R Vyas Leukemia Cancer Detection Using Image
Analytics:(Comparative Study) 2020 US Patent 10,628,720
14]
A Belhekar, K Gagare, R Bedse, Y Bhelkar, K Rajeswari, M Karthikeyan Assessing therapeutic potential of
molecules: molecular property diagnostic suite for tuberculosis
2019 2019 5th International Conference On Computing, Communication,
Control And …
15]
AS Gaur, A Bhardwaj, A Sharma, L John, MR Vivek, N Tripathi, M Karthikeyan,... Pharmacophore and docking based virtual
screening of validated Mycobacterium tuberculosis targets 2017 Journal of
Chemical Sciences 129, 515-531
16]
R Vyas, M Karthikeyan, G Nainaru, M Muthukrishnan Role of chemical reactivity and transition
state modeling for virtual screening 2015 Combinatorial Chemistry & High
Throughput Screening 18 (7), 624-637
17]
M Karthikeyan, R Vyas, S S Tambe,
D Radhamohan, B D Kulkarni A study of applications of
machine learning based classification methods for virtual screening of lead
molecules 2015 Combinatorial Chemistry & High Throughput Screening 18 (7),
638-657
18]
R Vyas, S Bapat, E Jain, S S
Tambe, M Karthikeyan, B D Kulkarni Protein Ligand
Complex Guided Approach for Virtual Screening 2015 Combinatorial Chemistry
& High Throughput Screening 18 (7), 658-672
19]
M Karthikeyan, D Pandit, R Vyas Editorial (Thematic
Issue: Design and Development of New Chemoinformatics
Tools for Virtual Screening) 2015 Combinatorial Chemistry & High Throughput
Screening 18 (6), 577-590
20]
M Karthikeyan, R Vyas Design and development of ChemInfoCloud:
an integrated cloud enabled platform for virtual screening 2015 Combinatorial
Chemistry & High Throughput Screening 18 (6), 526-527
21]
M Karthikeyan, D Pandit, A Bhavasar,
R Vyas Prediction of Bioactive Compounds Using Computed NMR Chemical Shifts
2015 Combinatorial Chemistry & High Throughput Screening 18 (6), 604-619
22]
M Karthikeyan, P Ramanpillai Rajamohanan,
R Vyas ChemScreener: A distributed computing tool for
scaffold based virtual screening 2015 Combinatorial Chemistry & High
Throughput Screening 18 (6), 562-576
23]
M Karthikeyan, D Pandit, R Vyas MegaMiner:
a tool for lead identification through text mining using chemoinformatics
tools and cloud computing environment 2015 Combinatorial chemistry & high
throughput screening 18 (6), 544-561
24]
M Karthikeyan, Y Pandit, D Pandit,
R Vyas Role of open source tools and resources in virtual screening for drug
discovery 2015 Combinatorial Chemistry & High Throughput Screening 18 (6),
591-603
25]
M Karthikeyan, R Vyas Special Issue on Chemoinformatics
(12 Articles) 2015 Combinatorial chemistry & high throughput screening 18
(6), 528-543
26]
M Mujahid, P Yogeeswari, D Sriram, UMV Basavanag, E Díaz-Cervantes, M Karthikeyan, Spirochromone-chalcone
conjugates as antitubercular agents: synthesis, bio
evaluation and molecular modeling studies 2015 RSC advances 5 (129),
106448-106460
27]
M Karthikeyan SIMULATED CARBON AND PROTON NMR CHEMICAL SHIFTS BASED BINARY
FINGERPRINTS FOR VIRTUAL SCREENING 2014 WO Patent WO 2014/207670 A1
(http://tinyurl.com/lgpayvu)
28]
M Karthikeyan, S Gajalakshmi, SA Abbasi
Effect of storage on the properties of vermicompost
generated from paper waste: with focus on pre-drying and extent of sealing 2014
International Journal of Energy and Environmental Engineering 5, 291-301
29]
R Vyas, P Goel, M Karthikeyan, SS Tambe,
BD Kulkarni Pharmacokinetic modeling of Caco-2 cell permeability using genetic
programming (GP) method 2014 Letters in Drug Design & Discovery 11 (9),
1112-1118
30]
M Karthikeyan chemical structure recognition tool 2014 US Patent US
2014/0301608 A1 (http://patentimages.storage.googleapis.com …
31]
M Karthikeyan ChemInfoCloud: Opensource
based Cloud compatible chemical textmining tools for
harvesting largescale medical literature 2014 ABSTRACTS OF PAPERS OF THE
AMERICAN CHEMICAL SOCIETY 248
32]
M Karthikeyan, R Vyas Machine Learning Methods in Chemoinformatics
for Drug Discovery 2014 Practical Chemoinformatics 1,
133-194
33]
M Karthikeyan, R Vyas Chemoinformatics Approach for
the Design and Screening of Focused Virtual Libraries 2014 Practical Chemoinformatics 1, 93-131
34]
M Karthikeyan, R Vyas Text-based chemical information locator from the internet
using commercial barcodes 2014 Practical Chemoinformatics,
1-92
35]
M Karthikeyan, R Vyas Practical chemoinformatics (A
Text Book) 2014 Springer
36]
M Karthikeyan, R Vyas Active Site-Directed Pose
Prediction Programs for Efficient Filtering of Molecules 2014 Practical Chemoinformatics, 271-316
37]
M Karthikeyan, R Vyas Chemical text mining for lead
discovery 2014 Practical chemoinformatics, 415-449
38]
M Karthikeyan, R Vyas Cloud computing infrastructure
development for chemoinformatics 2014 Practical Chemoinformatics, 501-528
39]
M Karthikeyan, R Vyas Representation, Fingerprinting,
and Modelling of Chemical Reactions 2014 Practical Chemoinformatics,
317-374
40]
M Karthikeyan, R Vyas Predictive Methods for Organic
Spectral Data Simulation 2014 Practical Chemoinformatics,
375-414
41]
M Karthikeyan, R Vyas Docking and Pharmacophore
Modelling for Virtual Screening 2014 Practical Chemoinformatics,
195-269
42]
M Karthikeyan, R Vyas Integration of automated workflow
in chemoinformatics for drug discovery 2014 Practical
Chemoinformatics, 451-499
43]
E Jain, M Karthikeyan, Y Pandit, D Pandit, G Nainaru, S Nalwade, R Vyas ChemTextMiner: An
open source tool kit for mining medical literature abstracts 2012 Nature Precedings, 1-1
46]
M Karthikeyan, R Vyas Chemical Structure Representations and Applications in
Computational Toxicity 2012 Computational Toxicology: Volume I, 167-192
47]
M Karthikeyan, Y Pandit, D Pandit,
G Nainaru, S Nalwade, R Vyas,
E Jain ChemTextMiner: An open source tool kit for
mining medical literature abstracts 2011 Nature Publishing Group
48]
M Karthikeyan Computer Vision based chemical information extraction from
digital images and streaming videos 2011 ABSTRACTS OF PAPERS OF THE AMERICAN
CHEMICAL SOCIETY 242
49]
M Karthikeyan, S Krishnan, AK Pandey, A Bender, A Tropsha
Distributed chemical computing using ChemStar: an
open source java remote method invocation architecture applied to large scale
molecular data from PubChem 2008 Journal of chemical information and modeling
48 (4), 691-703
50]
M Karthikeyan, S Krishnan, AK Pandey, A Bender Harvesting chemical information
from the Internet using a distributed approach: ChemXtreme
2006 Journal of chemical information and modeling 46 (2), 452-461
51]
M Karthikeyan Encoding and decoding of graphical chemical structure as
commercial barcodes 2005 GAP; 224026
52]
M Karthikeyan, A Bender Encoding and decoding graphical chemical structures as
two-dimensional (PDF417) barcodes 2005 Journal of chemical information and
modeling 45 (3), 572-580
53]
M Karthikeyan, RC Glen, A Bender General melting point prediction based on a
diverse compound data set and artificial neural networks 2005 Journal of
chemical information and modeling 45 (3), 581-590
54]
M Karthikeyan, S Krishnan Encoding and Decoding of chemical structures as
Commercial Barcodes 2005 Accepted for publication
55]
M Karthikeyan PharmTree 2.1 2003 Journal of Chemical
Information and Computer Sciences 43 (6), 2194-2195
56]
M Karthikeyan YChemoinformatics tools for
combinatorial chemistry 2003 ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL
SOCIETY 225, U558-U558
57]
M Karthikeyan, D Uzagare, S Krishnan Compressed
chemical markup language (CCML) for compact storage and inventory applications
2003 ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 225, U554-U554
58]
M Karthikeyan, S Krishnan, C Steinbeck Text-based chemical information locator
from the internet using commercial barcodes 2002 Abstracts of Papers of the
American Chemical Society 223, 72-CINF
59]
M Karthikeyan, D Uzagare, S Krishnan, M Yang, G Marchionini Searching Video Segments through Transcript,
Metadata, and SVG Objects 2002 Digital Libraries: People, Knowledge, and
Technology: 5th International …
60]
M Karthikeyan, S Krishnan Chemoinformatics: a tool
for modern drug discovery 2002 International journal of information technology
and management 1 (1), 69-82
61]
A Vishal, M Karthikeyan, EPZ-10 catalyzed regioselective
transformation of alkenes into β-iodo ethers, iodohydrins and 2-iodomethyl-2, 3-dihydrobenzofurans 2002
Green Chemistry 4 (4), 325-327
62]
G Pandey, M Karthikeyan, A Murugan New intramolecular
α-arylation strategy of ketones by the reaction
of silyl enol ethers to photosensitized electron transfer generated arene radical cations: construction of … 1998 The
Journal of Organic Chemistry 63 (9), 2867-2872
63]
M Karthikeyan Photoinduced electron transfer (PET)
promoted carboannulation strategy: arene radical cation in carbon-carbon bond formation
reaction 1998 CSIR-National Chemical Laboratory, Pune
64] G
Pandey, A Krishna, K Girija, M Karthikeyan
Intramolecular nucleophilic addition of silylenol
ether to photosensitized electron transfer (PET) generated arene
radical cations: a novel non-reagent based carboannulation …
1993 Tetrahedron letters 34 (41), 6631-6634
List of selected
US Patents Granted
1. WO/2013/030850 M Karthikeyan,
CHEMICAL STRUCTURE RECOGNITION TOOL WO - 07.03.2013, Int.Class , G06F 19/00, Appl.No PCT/IN2012/000567
2. 20160140326 M Karthikeyan,
SIMULATED CARBON AND PROTON NMR CHEMICAL SHIFTS BASED BINARY FINGERPRINTS FOR
VIRTUAL SCREENING
3. 20210210173 M Karthikeyan,
METHOD FOR HARVESTING 3D CHEMICAL STRUCTURES FROM FILE FORMATS US - 08.07.2021 Int.Class G16C 20/80 Appl.No
16072097
4. 201611011757 M Karthikeyan,
REMOTE MONITORING AND CONTROLLING PHYSICAL PARAMETERS OF A MATERIAL UNDER TRANSPORTATION
IN - 02.02.2018 Int.Class G06Q 10/08 Appl.No 201611011757
5. 12.
3527/DEL/2015 M Karthikeyan, AN AUTOMATED REMOTE COMPUTING METHOD AND SYSTEM BY EMAIL PLATFORM
FOR MOLECULAR ANALYSIS IN - 05.05.2017 Int.Class G06F
19/20 Appl.No 3527/DEL/2015
6.
Text Book: Practical M Karthikeyan, Chemoinformatics
Springer 2014 (ISBN: 978-81-322-1779-4)
http://www.springer.com/chemistry/book/978-81-322-1779-4
1.
Open-Source
Tools, Techniques, and Data in Chemoinformatics
Muthukumarasamy
Karthikeyan, Renu Vyas
Pages 1-92
2.
Chemoinformatics Approach for the Design and Screening of
Focused Virtual Libraries
Muthukumarasamy
Karthikeyan, Renu Vyas
Pages 93-131
3.
Machine
Learning Methods in Chemoinformatics for Drug
Discovery
Muthukumarasamy
Karthikeyan, Renu Vyas
Pages 133-194
4.
Docking
and Pharmacophore Modelling for Virtual Screening
Muthukumarasamy
Karthikeyan, Renu Vyas
Pages 195-269
5.
Active
Site-Directed Pose Prediction Programs for Efficient Filtering of Molecules
Muthukumarasamy
Karthikeyan, Renu Vyas
Pages 271-316
6.
Representation,
Fingerprinting, and Modelling of Chemical Reactions
Muthukumarasamy
Karthikeyan, Renu Vyas
Pages 317-374
7.
Predictive
Methods for Organic Spectral Data Simulation
Muthukumarasamy
Karthikeyan, Renu Vyas
Pages 375-414
8.
Chemical
Text Mining for Lead Discovery
Muthukumarasamy
Karthikeyan, Renu Vyas
Pages 415-449
9.
Integration
of Automated Workflow in Chemoinformatics for Drug
Discovery
Muthukumarasamy Karthikeyan,
Renu Vyas
Pages 451-499
10.
Cloud
Computing Infrastructure Development for Chemoinformatics
Muthukumarasamy
Karthikeyan, Renu Vyas
Pages 501-528
M Karthikeyan's Current Areas of research: Artificial
Intelligence: Pioneering Solutions Across Key Global Sectors
In the
rapidly evolving landscape of the 21st century, Artificial Intelligence (AI)
stands out as a beacon of innovation, heralding unprecedented advances across
an array of industries. By harnessing the potential of machine learning and
deep learning, AI delves deep into vast datasets, extracting insights and
catalyzing transformative solutions. Let's delve into the manifold advantages
of AI in reshaping crucial sectors:
1. Health: Personalized and Proactive Care
Predictive
Analysis: AI, through deep learning algorithms, can predict disease outbreaks,
patient admissions, and other crucial metrics, enabling healthcare systems to
be better prepared.
Precision
Medicine: Machine learning models can analyze genetic information to create
personalized treatment plans, catering specifically to an individual's genetic
makeup.
Automated
Diagnosis: With the ability to scan and interpret medical imagery, AI can
assist in the early detection of ailments, from tumors to retinal diseases.
2. Agriculture: A Revolution in Farming
Crop
Optimization: AI algorithms analyze weather patterns, soil quality, and crop
health to provide farmers with real-time advice on crop management.
Pest
Prediction: By assessing environmental conditions, AI can predict pest attacks,
aiding in timely interventions.
Harvesting
Robotics: Automated systems powered by AI can handle tasks from sowing seeds to
harvesting crops, optimizing yield and reducing waste.
3. Finance: Streamlined Operations and
Enhanced Security
Fraud
Detection: Machine learning models can identify and alert about anomalous
transaction activities in real-time, vastly reducing financial fraud.
Robo-Advisors:
By analyzing market data, AI-powered robo-advisors
offer investment recommendations tailored to individual preferences and risk
tolerances.
Credit
Scoring: AI provides more comprehensive and nuanced credit scoring by analyzing
non-traditional data sources, ensuring more accurate risk assessment.
4. Materials: Accelerated Discovery and
Design
Material
Prediction: AI can predict the properties of new materials before they are ever
synthesized in the lab.
Optimization:
Advanced models can tweak the properties of materials, aiding in the design of
products from more durable tires to efficient batteries.
Recycling
Innovations: AI can identify and sort recyclable materials more efficiently,
promoting a sustainable production ecosystem.
5. Sustainability: A Blueprint for a
Greener Future
Resource
Management: AI offers optimal utilization strategies for scarce resources, from
water in drought-prone areas to optimizing electricity in urban grids.
Waste
Reduction: Machine learning algorithms can predict and manage waste production
and disposal in urban areas.
Biodiversity
Conservation: AI can monitor and predict threats to ecosystems, aiding in
conservation efforts.
6. Energy: Smart Grids and Sustainable
Solutions
Demand
Forecasting: AI algorithms predict energy demands, allowing for efficient
allocation and reduced wastage.
Renewable
Energy Optimization: From optimizing the angle of solar panels throughout the
day to predicting wind patterns for turbines, AI ensures maximal renewable
energy harnessing.
Maintenance
Predictions: Predictive analysis identifies potential breakdowns in energy systems,
ensuring timely maintenance and reducing downtimes.
7. Environment: Monitoring, Management,
and Mitigation
Climate
Modeling: Deep learning models provide more accurate predictions of climate
change, informing global strategies.
Pollution
Control: AI systems monitor pollution in real-time, guiding interventions and
policy-making.
Conservation
Initiatives: Machine learning models track endangered species and
deforestation, providing data to drive conservation initiatives.
Other research projects with
investigators (M Karthikeyan:):
|
S.No |
Name
of the project (Project Investigator) |
Name
of funding agency |
Date
of commencement |
Date
of completion |
|
1 |
Barcoding
Chemical Structure |
DSIR
New Delhi |
2002 |
2004 |
|
2 |
MolTable Portal |
DSIR
New Delhi |
2006 |
2008 |
|
3 |
Chemoinformatics Cloud Platform for design of new materials |
DST
New Delhi |
2009 |
2013 |
|
4 |
GENESIS (Chemoinformatics,
Drug Discovery) |
CSIR
New Delhi |
2012 |
2017 |
|
5 |
INSPIRE (Chemoinformatics, Reaction Modeling) |
CSIR
New Delhi |
2012 |
2017 |
|
6 |
Chemoinformatics portal
for HEM (PI) |
DRDO |
2016 |
2019 |
|
7 |
CSIR Computer Cure Cancer AI (PI) |
CSIR
New Delhi |
2018 |
2020 |
|
8 |
CSIR SAGITA for Precision Agriculture (PI) |
CSIR
New Delhi |
2019 |
2020 |