Journal Of Computational Biology Research Articles

Special Issue Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC) Workshop (2022).

Journal of Computational BiologyAhead of Print PrefaceSpecial Issue Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC) Workshop (2022)Hyundoo Jeong, JOSÉ Lugo-martinez, Anna Ritz, Yijie Wang, and Chi ZhangHyundoo JeongAssistant Professor of Biomedical and Robotics Engineering, Incheon National University, Incheon, South Korea.Search for more papers by this author, JOSÉ Lugo-martinezAssistant Professor of Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.Search for more papers by this author, Anna RitzAddress correspondence to: Dr. Anna Ritz, Assoc. Prof., Department of Biology, Reed College, 3203 SE Woodstock Blvd., Portland, OR 97202, USA E-mail Address: aritz@reed.eduAssociate Professor of Biology, Reed College, Portland, Oregon, USA.Search for more papers by this author, Yijie WangAssistant Professor of Computer Science, Indiana University at Bloomington, Bloomington, Indiana, USA.Search for more papers by this author, and Chi ZhangAssistant Professor of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA.Search for more papers by this authorPublished Online:5 Jun 2023https://doi.org/10.1089/cmb.2023.29090.hjAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"Special Issue Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC) Workshop (2022)." Journal of Computational Biology, , pp. FiguresReferencesRelatedDetails Volume 0Issue 0 InformationCopyright 2023, Mary Ann Liebert, Inc., publishersTo cite this article:Hyundoo Jeong, JOSÉ Lugo-martinez, Anna Ritz, Yijie Wang, and Chi Zhang.Special Issue Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC) Workshop (2022).Journal of Computational Biology.ahead of printhttp://doi.org/10.1089/cmb.2023.29090.hjOnline Ahead of Print:June 5, 2023PDF download

Preface: MatBio 2021 Special Section

Journal of Computational BiologyVol. 30, No. 2 MatBio 2021 Special SectionPreface: MatBio 2021 Special SectionGUEST EDITORS: Mai Alzamel, Christopher Hampson, Costas Iliopoulos, and Fatima VayaniGUEST EDITORS: Mai AlzamelAddress correspondence to: Dr. Mai Alzamel, Department of Informatics, King's College London, Bush House, 30 Aldwych, London WC2B 4BG, United Kingdom, [Also: Department of Computer Science, King Saud University] Department of Informatics, King's College London, London, United Kingdom.Search for more papers by this author, Christopher HampsonAddress correspondence to: Dr. Christopher Hampson, Department of Informatics, King's College London, Bush House, 30 Aldwych, London WC2B 4BG, United Kingdom Department of Informatics, King's College London, London, United Kingdom.Search for more papers by this author, Costas IliopoulosAddress correspondence to: Prof. Costas Iliopoulos, Department of Informatics, King's College London, Bush House, 30 Aldwych, London WC2B 4BG, United Kingdom Department of Informatics, King's College London, London, United Kingdom.Search for more papers by this author, and Fatima VayaniAddress correspondence to: Dr. Fatima Vayani, Department of Informatics, King's College London, Bush House, 30 Aldwych, London WC2B 4BG, United Kingdom Department of Informatics, King's College London, London, United Kingdom.Search for more papers by this authorPublished Online:7 Feb 2023https://doi.org/10.1089/cmb.2023.29080.preAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"Preface: MatBio 2021 Special Section." Journal of Computational Biology, 30(2), p. 117FiguresReferencesRelatedDetails Volume 30Issue 2Feb 2023 InformationCopyright 2023, Mary Ann Liebert, Inc., publishersTo cite this article:GUEST EDITORS: Mai Alzamel, Christopher Hampson, Costas Iliopoulos, and Fatima Vayani.Preface: MatBio 2021 Special Section.Journal of Computational Biology.Feb 2023.117-117.http://doi.org/10.1089/cmb.2023.29080.prePublished in Volume: 30 Issue 2: February 7, 2023Online Ahead of Print:January 18, 2023PDF download

Michael Waterman's Contributions to Computational Biology and Bioinformatics.

On the occasion of Dr. Michael Waterman's 80th birthday, we review his major contributions to the field of computational biology and bioinformatics including the famous Smith-Waterman algorithm for sequence alignment, the probability and statistics theory related to sequence alignment, algorithms for sequence assembly, the Lander-Waterman model for genome physical mapping, combinatorics and predictions of ribonucleic acid structures, word counting statistics in molecular sequences, alignment-free sequence comparison, and algorithms for haplotype block partition and tagSNP selection related to the International HapMap Project. His books Introduction to Computational Biology: Maps, Sequences and Genomes for graduate students and Computational Genome Analysis: An Introduction geared toward undergraduate students played key roles in computational biology and bioinformatics education. We also highlight his efforts of building the computational biology and bioinformatics community as the founding editor of the Journal of Computational Biology and a founding member of the International Conference on Research in Computational Molecular Biology (RECOMB).

Estimation of the journal distance of Genomics & Informatics from other bioinformatics-driven journals, 2003-2018.

This study explored the trends of Genomics & Informatics during the period of 2003-2018 in comparison with 11 other scholarly journals: BMC Bioinformatics, Algorithms for Molecular Biology: AMB, BMC Systems Biology, Journal of Computational Biology, Briefings in Bioinformatics, BMC Genomics, Nucleic Acids Research, American Journal of Human Genetics, Oncogenesis, Disease Markers, and Microarrays. In total, 22,423 research articles were reviewed. Content analysis was the main method employed in the current research. The results were interpreted using descriptive analysis, a clustering analysis, word embedding, and deep learning techniques. Trends are discussed for the 12 journals, both individually and collectively. This is an extension of our previous study (PMCID: PMC6808643).

Preface Special Issue: RECOMB 2019

Journal of Computational BiologyVol. 27, No. 4 PrefacePreface Special Issue: RECOMB 2019Lenore J. CowenLenore J. CowenLenore J. Cowen, Professor of Computer Science and, Professor of Mathematics, Department of Computer Science, Tufts University E-mail Address: cowen@cs.tufts.eduSearch for more papers by this authorPublished Online:8 Apr 2020https://doi.org/10.1089/cmb.2020.29027.ljcAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"Preface Special Issue: RECOMB 2019." Journal of Computational Biology, 27(4), p. 441FiguresReferencesRelatedDetails Volume 27Issue 4Apr 2020 InformationCopyright 2020, Mary Ann Liebert, Inc., publishersTo cite this article:Lenore J. Cowen.Preface Special Issue: RECOMB 2019.Journal of Computational Biology.Apr 2020.441-441.http://doi.org/10.1089/cmb.2020.29027.ljcPublished in Volume: 27 Issue 4: April 8, 2020PDF download

Preface Special Issue: RECOMB 2018.

Journal of Computational BiologyVol. 27, No. 3 PrefaceFree AccessPreface Special Issue: RECOMB 2018Sorin IstrailSorin IstrailSorin Istrail, PhD, Co-Editor-in-Chief Search for more papers by this authorPublished Online:11 Mar 2020https://doi.org/10.1089/cmb.2020.29026.siAboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail RECOMB, the International Conference on Research in Computational Molecular Biology, was held on April 21–24, 2018, in Paris (https://recomb2018.fr/). This was the conference's 22nd edition. The conference is a series of well-established scientific conferences bridging the areas of computational, mathematical, statistical, and biological sciences. The conference featured keynote talks by pre-eminent scientists in life sciences, presentations of groundbreaking research in computational biology, selected over the course of a highly rigorous peer-review process, and poster sessions on the latest research progress. RECOMB 2018 was located at the International Conference Center (CICSU) of the Pierre and Marie Curie Campus of Sorbonne University in the historic Jussieu district of Paris. The conference was attended by 510 participants.Following a tradition started by Michael Waterman at the first conference, RECOMB 1997, the Journal of Computational Biology (JCB) has published every year the RECOMB/JCB Special Issue containing a set of articles in final form presented at that year's RECOMB conference.The present volume is the 2018 RECOMB/JCB Special Issue and contains 13 articles presented at the conference.FiguresReferencesRelatedDetails Volume 27Issue 3Mar 2020 InformationCopyright 2020, Mary Ann Liebert, Inc., publishersTo cite this article:Sorin Istrail.Preface Special Issue: RECOMB 2018.Journal of Computational Biology.Mar 2020.301-301.http://doi.org/10.1089/cmb.2020.29026.siPublished in Volume: 27 Issue 3: March 11, 2020PDF download

Retracted: Identification of Prognosis Biomarkers of Prostatic Cancer in a Cohort of 498 Patients from TCGA.

The article entitled, "Identification of prognosis biomarkers of prostatic cancer in a cohort of 498 patients from TCGA," by Chen Z and Hu H. (J Comput Biol Dec 2019: e-pub ahead of print; DOI: 10.1089/cmb.2019.0224) is being officially retracted at the authors' request due to errors found in the data after publication of the article. The detected errors render the results and conclusion irreproducible, and therefore, invalid. Based on the communications received from the authors, the editorial leadership of Journal of Computational Biology agreed to retract the published paper. However, after retracting the article, it was also discovered that the same article had been previously published in volume 43, issue 6 of the journal, Current Problems in Cancer, published by Elsevier. The publisher of Journal of Computational Biology was in communication with Elseivier since simultaneous submission and/or publication is a violation of the proper protocols of peer review, and they are conducting their own evaluation. Journal of Computational Biology also notified the authors' institution of the infraction. Journal of Computational Biology, its Editor, and its Publisher are committed to preserving the integrity of the scientific record for the community it serves.

Drug and Non-Drug Treatment Options of Fibromyalgia

Fibromyalgia (FM) treatment does not have a clear objective pathophysiological therapeutic goal. The management of this complex condition has thus perplexed the medical community for many years, and several national and international guidelines have aimed to address this complexity. Pain relieving pharmaceutical medications are generally connected with an assortment of unfriendly reactions, for example, constipation, urinary retention, nausea, sedation, respiratory depression, myoclonus, delirium, sexual dysfunction, and hyperalgesia. The challenge of achieving adequate pain control without adverse side effects further compounds the problem and provides rationale for seeking complementary medicine and non-medicine alternatives. Keywords: Fibromyalgia, chronic non-cancer pain, neurofeedback, cognitive behavioral therapy, acceptance and commitment therapy, inflammatory arthritis Cite this Article Abdul Kader Mohiuddin. Drug and Non drug Treatment Options of Fibromyalgia. Research & Reviews: Journal of Computational Biology. 2019; 8(3): 15 23 p.

Preface: Selected Articles of the Second International Conference on Algorithms for Computational Biology (AlCoB 2015).

Journal of Computational BiologyVol. 24, No. 2 Special Issue: Second International Conference on Algorithms for Computational Biology (AlCoB 2015)Preface: Selected Articles of the Second International Conference on Algorithms for Computational Biology (AlCoB 2015)Adrian-Horia Dediu and Carlos Martín-VideAdrian-Horia DediuSuperData, Bucharest, Romania.Search for more papers by this author and Carlos Martín-VideRovira i Virgili University, Tarragona, Spain.Search for more papers by this authorPublished Online:1 Feb 2017https://doi.org/10.1089/cmb.2017.29005.ahdAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"Preface: Selected Articles of the Second International Conference on Algorithms for Computational Biology (AlCoB 2015)." Journal of Computational Biology, 24(2), pp. 91–92FiguresReferencesRelatedDetails Volume 24Issue 2Feb 2017 InformationCopyright 2017, Mary Ann Liebert, Inc.To cite this article:Adrian-Horia Dediu and Carlos Martín-Vide.Preface: Selected Articles of the Second International Conference on Algorithms for Computational Biology (AlCoB 2015).Journal of Computational Biology.Feb 2017.91-92.http://doi.org/10.1089/cmb.2017.29005.ahdPublished in Volume: 24 Issue 2: February 1, 2017PDF download

RECOMB/ISCB systems biology, regulatory genomics, and DREAM 2013 special issue.

Journal of Computational BiologyVol. 21, No. 5 RECOMB/ISCB Systems Biology, Regulatory Genomics, and DREAM 2013 Special IssueGuest Editors: Andrea Califano, Manolis Kellis, and Gustavo StolovitzkyPrefaceRECOMB/ISCB Systems Biology, Regulatory Genomics, and DREAM 2013 Special IssueAndrea Califano, Manolis Kellis, and Gustavo StolovitzkyAndrea CalifanoDepartments of Systems Biology, Biochemistry & Molecular Biophysics, Biomedical Informatics, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York.Search for more papers by this author, Manolis KellisEngineering and Computer Science Department, Massachusetts Institute of Technology, Cambridge, Massachusetts.Search for more papers by this author, and Gustavo StolovitzkyTranslational Systems Biology and Nanobiotechnology, IBM Thomas J. Watson Research Center, Yorktown Heights, New York.Search for more papers by this authorPublished Online:30 Apr 2014https://doi.org/10.1089/cmb.2014.009pAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"RECOMB/ISCB Systems Biology, Regulatory Genomics, and DREAM 2013 Special Issue." Journal of Computational Biology, 21(5), pp. 371–372FiguresReferencesRelatedDetails Volume 21Issue 5May 2014 InformationCopyright 2014, Mary Ann Liebert, Inc.To cite this article:Andrea Califano, Manolis Kellis, and Gustavo Stolovitzky.RECOMB/ISCB Systems Biology, Regulatory Genomics, and DREAM 2013 Special Issue.Journal of Computational Biology.May 2014.371-372.http://doi.org/10.1089/cmb.2014.009pPublished in Volume: 21 Issue 5: April 30, 2014PDF download

Fine-Grained Parallel and Distributed Spatial Stochastic Simulation of Biological Reactions

Fine-Grained Parallel and Distributed Spatial Stochastic Simulation of Biological Reactions

A polynomial-time DNA computing solution for the Bin-Packing Problem

It is suggested here an algorithm based on stickers for the DNA Computing model [S. Roweis, E. Winfree, R. Burgoyne, N. Chelyapov, M. Goodman, P. Rothemund, L. Adleman, A sticker-based model for DNA Computation, Journal of Computational Biology 5 (1998) 615–629] that solves the well known Bin-Packing Problem (BPP), that belongs to the class NP -Hard in the strong sense, in a time bounded by O ( n 2 q ) , where n is the quantity of items and q the space requirements expressed in bits. To the best of the authors’ knowledge, this is the first polynomial time algorithmic solution for the BPP in such a model.

Genomics, molecular imaging, bioinformatics, and bio-nano-info integration are synergistic components of translational medicine and personalized healthcare research

Supported by National Science Foundation (NSF), International Society of Intelligent Biological Medicine (ISIBM), International Journal of Computational Biology and Drug Design and International Journal of Functional Informatics and Personalized Medicine, IEEE 7th Bioinformatics and Bioengineering attracted more than 600 papers and 500 researchers and medical doctors. It was the only synergistic inter/multidisciplinary IEEE conference with 24 Keynote Lectures, 7 Tutorials, 5 Cutting-Edge Research Workshops and 32 Scientific Sessions including 11 Special Research Interest Sessions that were designed dynamically at Harvard in response to the current research trends and advances. The committee was very grateful for the IEEE Plenary Keynote Lectures given by: Dr. A. Keith Dunker (Indiana), Dr. Jun Liu (Harvard), Dr. Brian Athey (Michigan), Dr. Mark Borodovsky (Georgia Tech and President of ISIBM), Dr. Hamid Arabnia (Georgia and Vice-President of ISIBM), Dr. Ruzena Bajcsy (Berkeley and Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Chih-Ming Ho (UCLA and Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Andy Baxevanis (United States National Institutes of Health), Dr. Arif Ghafoor (Purdue), Dr. John Quackenbush (Harvard), Dr. Eric Jakobsson (UIUC), Dr. Vladimir Uversky (Indiana), Dr. Laura Elnitski (United States National Institutes of Health) and other world-class scientific leaders. The Harvard meeting was a large academic event 100% full-sponsored by IEEE financially and academically. After a rigorous peer-review process, the committee selected 27 high-quality research papers from 600 submissions. The committee is grateful for contributions from keynote speakers Dr. Russ Altman (IEEE BIBM conference keynote lecturer on combining simulation and machine learning to recognize function in 4D), Dr. Mary Qu Yang (IEEE BIBM workshop keynote lecturer on new initiatives of detecting microscopic disease using machine learning and molecular biology, http://ieeexplore.ieee.org/servlet/opac?punumber=4425386) and Dr. Jack Y. Yang (IEEE BIBM workshop keynote lecturer on data mining and knowledge discovery in translational medicine) from the first IEEE Computer Society BioInformatics and BioMedicine (IEEE BIBM) international conference and workshops, November 2-4, 2007, Silicon Valley, California, USA.

Faspad: fast signaling pathway detection

Faspad is a user-friendly tool that detects candidates for linear signaling pathways in protein interaction networks based on an approach by Scott et al. (Journal of Computational Biology, 2006). Using recent algorithmic insights, it can solve the underlying NP-hard problem quite fast: for protein networks of typical size (several thousand nodes), pathway candidates of length up to 13 proteins can be found within seconds and with a 99.9% probability of optimality. Faspad graphically displays all candidates that are found; for evaluation and comparison purposes, an overlay of several candidates and the surrounding network context can also be shown. Faspad is available as free software under the GPL license at http://theinf1.informatik.uni-jena.de/faspad/ and runs under Linux and Windows.

Preface: Special RECOMB 2001 Issue

This issue of the Journal of Computational Biology contains a selection of papers that were presented at the Fifth Annual International Conference on Computational Biology RECOMB 2001, held in Montreal, Quebec, Canada on April 22–25, 2001. The RECOMB series was started in 1997 by Sorin Istrail, Pavel Pevzner, and Michael Waterman. RECOMB ’97 was held in Santa Fe, New Mexico, RECOMB ’98 was held in New York City, RECOMB ’99 took place in Lyon, France, and RECOMB 2000 was held in Tokyo, Japan. Selections of papers from these conferences appeared in Volume 4, Number 3–4; Volume 5, Number 3; Volume 6, Number 3–4; and Volume 7, Number 3–4. The call for papers for RECOMB 2001 gave rise to 128 submissions, out of which the program committee selected 35 papers to be presented at the conference. The extended abstracts of all accepted papers were published in the Proceedings of RECOMB 2001 (ACM Press). Full versions of 17 papers are contained in this volume. RECOMB 2001 had nine invited speakers: Mark Adams (Celera Genomics, Rockville, Maryland), Roger Brent (Molecular Sciences Institute, Berkeley, California), George Church (Harvard University, Cambridge, Massachusetts), Franz Lang (Universite de Montreal, Quebec, Canada), Klaus Lindpaintner (HoffmannLa Roche, Basel, Switzerland), Yvonne Martin (Abbott Laboratories, Abbott Park, Illinois), Mark Ptashne (Memorial Sloan Kettering Cancer Center, New York, New York), Philip Sharp (Massachusetts Institute of Technology, Cambridge, Massachusetts) and Mathias Wilm (European Molecular Biology Laboratory, Heidelberg, Germany). The Stanislaw Ulam Memorial Lecture was given by George Church. The Distinguished Biology Lecture was given by Philip Sharp. The Distinguished New Technologies Lecture was given by Mark Adams. The program committee consisted of Steve Bryant, Philipp Bucher, Gordon Crippen, Antoine Danchin, Sridhar Hannenhalli, David Haussler, Liisa Holm, Sorin Istrail, Minoru Kanehisa, Richard Karp, Thomas Lengauer, Hans-Peter Lenhof, Michal Linial, Satoru Miyano, Pavel Pevzner, Isidore Rigoutsos, David Sankoff, Ron Shamir, Donna Slonim, Terry Speed, Mike Sternberg, William Taylor, Martin Vingron, Tandy Warnow, Michael Waterman and Ralf Zimmer. The RECOMB 2001 program had three components: the invited keynotes, the contributed talks, and the poster session. The lively poster session was an important ingredient of the conference program. The collection of abstracts of the accepted posters appeared as a book, Currents in Computational Molecular Biology 2001, Nadia El-Mabrouk, Thomas Lengauer, David Sankoff, eds., that was published by Les Publications CRM, Montreal, Canada. The senior supporters for RECOMB 2001 included the governmental agencies US Department of Energy and US National Science Foundation, the Quebec Ministere de l’Industrie et du Commerce, the Centre de recherches mathematiques at Universite de Montreal, and the German National Research Center for Information Technology (GMD), as well as the companies Celera Genomics, Compaq, and Lion Bioscience. Additional support came from the International Society for Computational Biology (ISCB), the Centre de recherche en calcul applique (CERCA) in Montreal, and the companies Aventis Pharma and SmithKline Beecham. The conference was organized by the Universite de Montreal which also supported the conference in many ways. David Sankoff headed the local organization. The steering committee for the RECOMB conference series consists of Sorin Istrail, General Vice-Chair (Celera Genomics), Richard Karp (University of California, Berkeley), Thomas Lengauer (Max-Planck Institute for Informatics, Saarbrucken, Germany), Pavel Pevzner, General Chair (University of California,

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