Relevant bibliographies by topics / Biological Sciences

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Biological Sciences'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 June 2025

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Journal articles on the topic "Biological Sciences"

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Hoffmann, Antoni, and Wolf-Ernst Reif. "The methodology of the biological sciences: From an evolutionary biological perspective." Neues Jahrbuch für Geologie und Paläontologie - Abhandlungen 177, no. 2 (December 9, 1988): 185–211. http://dx.doi.org/10.1127/njgpa/177/1988/185.

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LATCHMAN, D. "Biological sciences." Lancet 336, no. 8722 (October 1990): 1054. http://dx.doi.org/10.1016/0140-6736(90)92507-e.

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HIEDA, Kotaro. "Spectroscopy in biological sciences. IV. Use of synchrotron radiation in biological sciencies." Journal of the Spectroscopical Society of Japan 36, no. 4 (1987): 295–305. http://dx.doi.org/10.5111/bunkou.36.295.

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Nethercott, Sally. "Biological sciences undervalued." Nursing Standard 9, no. 51 (September 13, 1995): 46. http://dx.doi.org/10.7748/ns.9.51.46.s44.

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Hong, Y. C., L. C. Chow, and W. E. Brown. "Basic Biological Sciences." Journal of Dental Research 64, no. 2 (February 1985): 82–84. http://dx.doi.org/10.1177/00220345850640021401.

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Lowenberg, B. F., J. E. Aubin, D. A. Deporter, J. Sodek, and A. H. Melcher. "Basic Biological Sciences." Journal of Dental Research 64, no. 9 (September 1985): 1106–10. http://dx.doi.org/10.1177/00220345850640090101.

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Wells, B. R., and H. Birkedal-Hansen. "Basic Biological Sciences." Journal of Dental Research 64, no. 10 (October 1985): 1186–90. http://dx.doi.org/10.1177/00220345850640100101.

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ERICKSON, BRITT. "BIOLOGICAL SCIENCES STANDARDS." Chemical & Engineering News 86, no. 44 (November 3, 2008): 21. http://dx.doi.org/10.1021/cen-v086n044.p021.

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KITAGAWA, Teizo, and Takashi OGURA. "Spectroscopy in biological sciences. II Raman spectroscopy in biological sciences." Journal of the Spectroscopical Society of Japan 36, no. 2 (1987): 147–62. http://dx.doi.org/10.5111/bunkou.36.147.

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Curtis, Vickie. "Online citizen science games: Opportunities for the biological sciences." Applied & Translational Genomics 3, no. 4 (December 2014): 90–94. http://dx.doi.org/10.1016/j.atg.2014.07.001.

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Dissertations / Theses on the topic "Biological Sciences"

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Wei, Fang. "The Explanatory Autonomy of the Biological Sciences." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/16855.

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This thesis aims to argue for the explanatory autonomy of the biological sciences. According to many philosophers and scientists, the biological sciences do not have their own explanatory autonomy because they either can be reduced to other “hard” sciences such as physics and chemistry, or cannot really explain phenomena since they do not have laws of nature. To maintain the explanatory autonomy of the biological sciences, I first argue against one influential form of reductionism, i.e., explanatory reductionism, by showing that explanation in the biological sciences can be achieved without reduction. Then, I demonstrate that the biological sciences do not have laws of nature. Instead, I suggest that it is usually biological models that do the explanatory work. Given the fact that biological models usually do the explanatory work, we still need a story of how biological models can be explanatory. However, to understand how a biological model can explain phenomena in the world, we first need to understand what the model-world relationship is. To this end, a holistic view of the model-world relationship is developed by looking closely at scientific practice. Based on this, a holistic account of model explanation is proposed. The basic idea behind the holistic account of model explanation is that, for a model to be explanatory, it must answer two kinds of questions: counterfactual dependence questions (corresponding to Woodward’s what-if-things-had-been-different questions, “w-questions” for short) that concern the model itself, and hypothetical questions that concern the relationship between the model and its target system. Furthermore, I suggest that the reason a biological model can answer these two kinds of questions is due to the fact that: (a) a model is a structure, that is, a set of dependence relationships that can be employed to answer w-questions, and that (b) the holistic fit between the model and its target warrants the hypothetical inference from the model to its target and thus helps to answer the second kind of question.
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Burrows, Andrea C. "A social study of women in contemporary biological sciences." Diss., This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-07282008-135540/.

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Edjoc, Rojiemiahd. "Movement interference effects during the tracking of biological and non biological movement." Thesis, University of Ottawa (Canada), 2007. http://hdl.handle.net/10393/27840.

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Are the neural and behavioural mechanisms underlying the tracking of another human's movement different from that of tracking the movement of a non-biological system? In an experiment by Kilner, Pauligan, Blakemore, (2003) an interference effect was found during the observation and tracking of incongruent biological movements (another human performing a different action), but not so with incongruent nonbiological movements (a robot performing a different action). They defined this interference effect as the degree of change in the movement trajectory of the observer due to observed movement. Recent studies have shown that interference of this kind was subject to both biological and non biological stimuli. However, the question of whether a similar interference effect is present during the observation of movements that possess the same invariant characteristics of human movement such as minimum jerk trajectories with bell-shaped velocity profiles but are not produced by a human (Flash & Hogan, 1985) has not been previously addressed. The present experiment asked eight participants to perform vertical and horizontal movements either congruently or incongruently to novel non-biological movement stimuli sets that resemble human movement (added invariant characteristics) ranging from point light displays to 3D virtual models of humans. This was followed by an interpersonal task while tracking the movements of a human experimenter. Results demonstrated that a congruency effect was observed where incongruent human movements exhibited the most interference. In other conditions, similar congruency effects were observed where the magnitude of the interference was dependent on the biological similarity of the stimuli to actual human movement. Also a main effect of "biologicalness" (Sinusoidal vs. Sinusoidal with noise vs. Minimum Jerk), type (3d human vs. Human) and a main interaction of type and congruency (3d human vs. Human) were observed. We argue that the central nervous system is highly attuned to biological characteristics at the most deep-rooted level. It seems that biological characteristics such as movement optimality leading to the abstract representation of human movement are tightly coupled as they elicit similar interference effects as tracking movements performed by a human.
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Ma, Yong. "THz time domain spectroscopy and its application in biological sciences." Thesis, University of Essex, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.496274.

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Arvestad, Lars. "Algorithms for biological sequence alignment." Doctoral thesis, KTH, Numerisk analys och datalogi, NADA, 1999. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-2905.

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Murrel, Benjamin. "Improved models of biological sequence evolution." Thesis, Stellenbosch : Stellenbosch University, 2012. http://hdl.handle.net/10019.1/71870.

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Thesis (PhD)--Stellenbosch University, 2012.<br>ENGLISH ABSTRACT: Computational molecular evolution is a field that attempts to characterize how genetic sequences evolve over phylogenetic trees – the branching processes that describe the patterns of genetic inheritance in living organisms. It has a long history of developing progressively more sophisticated stochastic models of evolution. Through a probabilist’s lens, this can be seen as a search for more appropriate ways to parameterize discrete state continuous time Markov chains to better encode biological reality, matching the historical processes that created empirical data sets, and creating useful tools that allow biologists to test specific hypotheses about the evolution of the organisms or the genes that interest them. This dissertation is an attempt to fill some of the gaps that persist in the literature, solving what we see as existing open problems. The overarching theme of this work is how to better model variation in the action of natural selection at multiple levels: across genes, between sites, and over time. Through four published journal articles and a fifth in preparation, we present amino acid and codon models that improve upon existing approaches, providing better descriptions of the process of natural selection and better tools to detect adaptive evolution.<br>AFRIKAANSE OPSOMMING: Komputasionele molekulêre evolusie is ’n navorsingsarea wat poog om die evolusie van genetiese sekwensies oor filogenetiese bome – die vertakkende prosesse wat die patrone van genetiese oorerwing in lewende organismes beskryf – te karakteriseer. Dit het ’n lang geskiedenis waartydens al hoe meer gesofistikeerde waarskynlikheidsmodelle van evolusie ontwikkel is. Deur die lens van waarskynlikheidsleer kan hierdie proses gesien word as ’n soektog na meer gepasde metodes om diskrete-toestand kontinuë-tyd Markov kettings te parametriseer ten einde biologiese realiteit beter te enkodeer – op so ’n manier dat die historiese prosesse wat tot die vorming van biologiese sekwensies gelei het nageboots word, en dat nuttige metodes geskep word wat bioloë toelaat om spesifieke hipotesisse met betrekking tot die evolusie van belanghebbende organismes of gene te toets. Hierdie proefskrif is ’n poging om sommige van die gapings wat in die literatuur bestaan in te vul en bestaande oop probleme op te los. Die oorkoepelende tema is verbeterde modellering van variasie in die werking van natuurlike seleksie op verskeie vlakke: variasie van geen tot geen, variasie tussen posisies in gene en variasie oor tyd. Deur middel van vier gepubliseerde joernaalartikels en ’n vyfde artikel in voorbereiding, bied ons aminosuur- en kodon-modelle aan wat verbeter op bestaande benaderings – hierdie modelle verskaf beter beskrywings van die proses van natuurlike seleksie sowel as beter metodes om gevalle van aanpassing in evolusie te vind.
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Au, Y. C. "Synthesising heterogeneity : trends of visuality in biological sciences, circa 1970s-2000s." Thesis, University College London (University of London), 2016. http://discovery.ucl.ac.uk/1478180/.

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This is a case study of diagrams in a field of biological mechanism research (apoptosis), revealing that mechanism diagrams play a crucial role in the practice of developing mechanistic explanations for cell biology. This thesis supports and extends the existing literature in the following aspects: the relationship between scientific representation and practice (Daston and Galison, 2007), inter-field and inter-level integration in biological practice of mechanism research (Bechtel, 2006; Craver and Darden, 2013), and the assertive and engaging power of diagrams (Bender and Marrinan, 2010; Wood, 1992, 2010). The methodology is composed of two parts: quantitative and qualitative. The quantification draws the comprehensive patterns of diagram use via analysing the coverage of diagrams. The qualitative part analyses three layers of the diagrams: visual element, composition, and style. This part contextualises the diagrams in four senses: source of ideas, perspective, adjacent text, scope of research. The results and the interpretation of results are also composed of quantitative and qualitative parts. The quantitative part shows a noticeable prevalence of two themes of diagrams: object and mechanism. The former reflects an interest in manipulating entities. The latter reflects an interest in integration of, and interaction between, different perspectives. The relative changes in the coverage of these two themes suggest a shift in the focus of practice from manipulation of biological entities toward inter-field interaction between heterogeneous perspectives. The qualitative part contains a central argument and several interesting discoveries. The central argument is that mechanism diagrams synthesise heterogeneity and thus have the power to assert novel ideas and engage real-world practice. The heterogeneity of perspectives is embedded in the practice of developing the cell models. The term “synthesis” means that novel meanings emerge from the integration of existing perspectives. This novelty of meanings attributes to the assertive power of mechanism diagrams. The engaging power facilitates interaction amongst the component perspectives, which is an important feature of mechanism research. In sum, this argument can explain the increasing reliance upon diagrams found in the quantitative results. The other interesting qualitative discoveries include but are not limited to the following. Firstly, biological diagrams can go beyond visual resemblance to entities. Secondly, there are many creative ways of making diagrams, such as importing visual vocabulary from non-specialist areas and modular use of visual elements. These creative ways show that visual conventions in biological diagrams are not given but undergo evolution, probably responding to the growing complexity of ideas. Thirdly, the evolution of biological visualisation is not merely driven by development of technology but embodies the interaction between ideas and technological advancement. The conclusion of this study treats mechanism diagrams as both epistemological and communicative devices acting in the research dynamics. The communication is part of the processes of knowing and intervening, taking place both horizontally and longitudinally. The horizontal communication is amongst different research groups in the field. The longitudinal communication is between different stages of model developing by the same individuals. Diagrams serve in the constant defining and redefining of boundary of research arenas through bringing about new problems and activating future research.
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Cramer, Karla B. "Impact of constructivism via the biological sciences curriculum study (BSCS) 5E model on student science achievement and attitude." Montana State University, 2012. http://etd.lib.montana.edu/etd/2012/cramer/CramerK0812.pdf.

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The investigation involved implementing constructivist instruction via the Biological Sciences Curriculum Study 5E Instructional Model to determine its' impact on student achievement and attitude. The study included 68 seventh grade Life Science students of average to above average achievement at a community based K-12 school in Florence, Montana. Treatment was implemented during a six week biome unit in which student achievement was assessed through the Evaluation Association Measured Academic Progress and summative assessments. Student attitude was evaluated through the Test of Science Related Attitudes and learning preference surveys, pre- and post-treatment. The effectiveness of constructivism approach to instruction on achievement via the BSCS 5E Instructional Model in the science classroom was not conclusively supported by data.
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Westbrooks, Kelly Anthony. "Biological Inference using Flow Networks." Digital Archive @ GSU, 2009. http://digitalarchive.gsu.edu/cs_diss/36.

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Many bioinformatics problems are inference problems: Given partial or incomplete information about something, use that information to infer the missing or unknown data. This work addresses two inference problems in bioinformatics. The rst problem is inferring viral quasispecies sequences and their frequencies from 454 pyrosequencing reads. The second problem is inferring the structure of signal transduction networks from observations of interactions between cellular components. At first glance, these problems appear to be unrelated to each other. However, this work successfully penetrates both problems using the machinery of ow networks and transitive reduction, tools from classical computer science that prove useful in a wide array of application domains.
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Goldstein, Goldie L. "Smart Temporal Phase Unwrapping for Biological Objects." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/311573.

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The development of a quantitative phase microscope (QPM) has allowed the ability to acquire real-time phase movies of biological processes. The image processing of the data is critical to the system's ability to measure relative changes. The phase data must be consistent throughout a measurement and background fluctuations must be minimized. The research presented in this work discusses methods to effectively process sequences of phase data such that it can be used to quantify changes within real-time studies of living cells. This work begins by exploring two-dimensional phase unwrapping to determine the most effective ways to estimate the measured phase surface. Conventional methods of comparing unwrapping performance will be used. In addition, a novel method will be introduced that can characterize accuracy using continuity of derivatives. It will be shown that the most accurate phase estimates are made using modulation data with quality-guided phase unwrapping. After two-dimensionally unwrapping all frames of data within a measurement, there are background fluctuations due to residual surface shape as well as mean phase value fluctuations. Traditionally, manual background removal methods are implemented. Due to the large streams of data that need to be analyzed for the QPM, an automated background removal method is introduced that automatically discriminates the background from features of interest and characterizes and removes the background shape from all frames within a sequence of data. No user intervention is required and the performance rivals manual methods. The final step in processing data from a QPM is to ensure consistent phase unwrapping over an entire dataset. This is a previously undiscussed topic within the field of quantitative phase microscopy. The two-dimensional phase unwrapping methods result in reasonable phase estimates of the measured sample however there are often inconsistencies in local regions amongst sequential frames of data. This work introduces a new method, Smart Temporal unwrapping that minimizes temporal inconsistencies. The image processing methods presented in this work combine to allow phase data acquired using a QPM to quantify relative changes in biological samples. These processing steps effectively minimize errors due to system vibration, residual measurement aberration, and phase unwrapping inconsistencies.
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Books on the topic "Biological Sciences"

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University of Cambridge. Local Examinations Syndicate. Biological sciences. Cambridge: University of Cambridge, 1997.

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Royal Society (Great Britain). Proceedings: Biological sciences. London: Royal Society of London, 1990.

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Challenor, Sally. Biological physics. Delhi: Global Media, 2009.

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Buican, D., and D. Thieffry, eds. Biological and Medical Sciences. Turnhout: Brepols Publishers, 2002. http://dx.doi.org/10.1484/m.dda-eb.5.112469.

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National Research Council of Canada. Division of Biological Sciences. S.l: s.n, 1985.

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V, Dashek William, and McMillin David, eds. Biological environmental science. Enfield, NH: Science Publishers, 2008.

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Ghosh, Shyamasree, and Rathi Dasgupta. Machine Learning in Biological Sciences. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8881-2.

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Hammes, Gordon G. Spectroscopy for the Biological Sciences. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471733555.

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Hammes, Gordon G. Spectroscopy for the Biological Sciences. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471733555.

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Stefan Banach International Mathematical Center and Instytut Matematyczny (Polska Akademia Nauk), eds. Stochastic models in biological sciences. Warszawa: Polish Academy of Sciences, Institute of Mathematics, 2008.

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Book chapters on the topic "Biological Sciences"

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Miller, Seumas. "Biological Sciences." In Dual Use Science and Technology, Ethics and Weapons of Mass Destruction, 105–14. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92606-3_8.

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Birke, Lynda. "Biological sciences." In A Companion to Feminist Philosophy, 194–203. Oxford, UK: Blackwell Publishing Ltd, 2017. http://dx.doi.org/10.1002/9781405164498.ch19.

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Clayton, Philip. "The Biological Sciences." In Religion and Science, 88–107. 2 [edition]. | New York : Routledge, 2018. | Series: The basics: Routledge, 2018. http://dx.doi.org/10.4324/9781315121277-5.

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Richardson, Angelique. "The Biological Sciences." In A Companion to Modernist Literature and Culture, 50–65. Oxford, UK: Blackwell Publishing Ltd, 2007. http://dx.doi.org/10.1002/9780470996331.ch6.

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Payne, Roger. "Experiments in Biological Sciences." In Research Methods for Postgraduates: Third Edition, 193–201. Oxford, UK: John Wiley & Sons, Ltd, 2016. http://dx.doi.org/10.1002/9781118763025.ch20.

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Ellis, Alan. "Social and Biological Sciences." In The Harvey Milk Institute Guide to Lesbian, Gay, Bisexual, Transgender, and Queer Internet Research, 101–13. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003421238-9.

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Kato, Goro C. "Cognitive and Biological Sciences." In Temporal Topos Methods for the Philosophy of Natural Sciences, 59–75. Singapore: Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2420-1_4.

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Meyerson, Émile. "Biological Phenomena." In Explanation in the Sciences, 177–205. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3414-9_7.

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Giering, Sarah L. C., and Matthew P. Humphreys. "Biological Pump." In Encyclopedia of Earth Sciences Series, 1–6. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-39193-9_154-1.

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Giering, Sarah L. C., and Matthew P. Humphreys. "Biological Pump." In Encyclopedia of Earth Sciences Series, 111–16. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-39312-4_154.

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Conference papers on the topic "Biological Sciences"

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Karastoyanov, Dimitar, and Elena Blagoeva. "3D Printing of Biological Materials." In 2024 9th International Conference on Mathematics and Computers in Sciences and Industry (MCSI), 188–91. IEEE, 2024. https://doi.org/10.1109/mcsi63438.2024.00038.

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Polsky, Igor. "BIOLOGICAL SCIENCES SOFTWARE ENVIRONMENT." In Theoretical and practical aspects of the formation of scientific area. Publishing House “Baltija Publishing”, 2025. https://doi.org/10.30525/978-9934-26-536-5-2.

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"Permutation Tests for Biological Sciences." In Dec. 12-14, 2022 Lisbon (Portugal). Excellence in Research & Innovation in Education, 2022. http://dx.doi.org/10.17758/eirai16.f1222214.

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WOOLEY, JOHN C. "CYBERINFRASTRUCTURE FOR THE BIOLOGICAL SCIENCES (CIBIO)." In Proceedings of the 2nd International Life Science Grid Workshop, LSGRID 2005. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812772503_0002.

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Bajaj, Chandrajit. "Quantitative visualization in the computational biological sciences." In 2012 IEEE Pacific Visualization Symposium (PacificVis). IEEE, 2012. http://dx.doi.org/10.1109/pacificvis.2012.6183567.

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"International Congress of Biological and Health Sciences." In International Congress of Biological and Health Sciences. Atena Editora, 2024. http://dx.doi.org/10.22533/at.ed.3282417051.

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Campanella, Luigi. "New frontiers of sensoristic sciences." In Optical Technologies for Industrial, Environmental, and Biological Sensing, edited by Tuan Vo-Dinh, Guenter Gauglitz, Robert A. Lieberman, Klaus P. Schaefer, and Dennis K. Killinger. SPIE, 2004. http://dx.doi.org/10.1117/12.524551.

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Dholakia, Kishan, Michael McDonald, and Gabriel C. Spalding. "Tailored optical landscapes for biological and colloidal sciences." In Biomedical Optics 2004, edited by Dan V. Nicolau, Joerg Enderlein, Robert C. Leif, and Daniel L. Farkas. SPIE, 2004. http://dx.doi.org/10.1117/12.533195.

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Oehmen, Christopher S., Mudita Singhal, Anuj Shah, Kyle Klicker, Lee Ann McCue, Joshua N. Adkins, Katrina Waters, et al. "Analytics challenge---High-throughput visual analytics biological sciences." In the 2006 ACM/IEEE conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1188455.1188769.

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Foster, F. Stuart. "Micro-ultrasound takes off (In the biological sciences)." In 2008 IEEE Ultrasonics Symposium (IUS). IEEE, 2008. http://dx.doi.org/10.1109/ultsym.2008.0029.

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Reports on the topic "Biological Sciences"

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Caffee, M. W., A. Marchetti, J. McAninch, and J. S. Vogel. Tracer-isotope development in environmental and biological sciences. Office of Scientific and Technical Information (OSTI), February 1999. http://dx.doi.org/10.2172/8052.

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Oskolkov, Nikolay. Deep Learning for the Life Sciences. Instats Inc., 2024. https://doi.org/10.61700/zjxxse1x3u05y1846.

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This intensive workshop provides a comprehensive exploration of deep learning applications in life sciences, focusing on practical techniques for analyzing complex biological datasets. Participants will gain theoretical and hands-on experience with deep learning tools such as TensorFlow and Keras, learning to construct neural networks and apply them to areas like genomics and personalized medicine.
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Oskolkov, Nikolay. Dimension Reduction Methods for Life Sciences. Instats Inc., 2024. http://dx.doi.org/10.61700/gyxh9ued08xio1347.

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This seminar provides a comprehensive overview of dimension reduction techniques in R and Python for high-dimensional biological data, focusing on their practical applications in life sciences. Participants will gain both theoretical knowledge and practical experience in linear and nonlinear dimensionality reduction methods such as tSNE and UMAP, enhancing their ability to analyze complex datasets effectively. By the conclusion of the seminar, participants will understand the theoretical and practical foundations of these methods, with a wealth of examples that can be rapidly applied for their own research problems.
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Geernaert, Gary, Shaima Nasiri, Jeff Stehr, Ashley Williamson, Sally McFarlane, Rick Petty, Xujing Davis, et al. Biological and Environmental Research, Earth and Environmental Systems Sciences Division (formerly Climate and Environmental Sciences Division) Strategic Plan: 2018–2023. Office of Scientific and Technical Information (OSTI), May 2018. http://dx.doi.org/10.2172/1616535.

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Chaudhary, Aashish. OPEN SOURCE SCALABLE DATA SERVICES AND DATA FUSION FOR BIOLOGICAL AND ENVIRONMENTAL SCIENCES. Office of Scientific and Technical Information (OSTI), March 2020. http://dx.doi.org/10.2172/1602442.

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Rodriguez Muxica, Natalia. Open configuration options Bioinformatics for Researchers in Life Sciences: Tools and Learning Resources. Inter-American Development Bank, February 2022. http://dx.doi.org/10.18235/0003982.

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The COVID-19 pandemic has shown that bioinformatics--a multidisciplinary field that combines biological knowledge with computer programming concerned with the acquisition, storage, analysis, and dissemination of biological data--has a fundamental role in scientific research strategies in all disciplines involved in fighting the virus and its variants. It aids in sequencing and annotating genomes and their observed mutations; analyzing gene and protein expression; simulation and modeling of DNA, RNA, proteins and biomolecular interactions; and mining of biological literature, among many other critical areas of research. Studies suggest that bioinformatics skills in the Latin American and Caribbean region are relatively incipient, and thus its scientific systems cannot take full advantage of the increasing availability of bioinformatic tools and data. This dataset is a catalog of bioinformatics software for researchers and professionals working in life sciences. It includes more than 300 different tools for varied uses, such as data analysis, visualization, repositories and databases, data storage services, scientific communication, marketplace and collaboration, and lab resource management. Most tools are available as web-based or desktop applications, while others are programming libraries. It also includes 10 suggested entries for other third-party repositories that could be of use.
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7

Kristofferson, D., and D. Mack. The BIOSCI electronic newsgroup network for the biological sciences. Final report, October 1, 1992--June 30, 1996. Office of Scientific and Technical Information (OSTI), October 1996. http://dx.doi.org/10.2172/376397.

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8

Mather, James, Raymond McCord, Doug Sisterson, and Jimmy Voyles. Biological and Environmental Research: Climate and Environmental Sciences Division: U.S./European Workshop on Climate Change Challenges and Observations. Office of Scientific and Technical Information (OSTI), November 2012. http://dx.doi.org/10.2172/1104854.

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9

Joel Cracraft and Richard O'Grady. Biological Sciences for the 21st Century: Meeting the Challenges of Sustainable Development in an Era of Global Change. Office of Scientific and Technical Information (OSTI), May 2007. http://dx.doi.org/10.2172/1032494.

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10

Revill, James, and Kai Ilchmann. Assessing the SecBio Platform Proposal for the Biological Weapons Convention. UNIDIR, December 2022. http://dx.doi.org/10.37559/wmd/22/bwc/04.

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Biosecurity and biosafety are important aspects of the life sciences and they have been discussed in the Biological Weapons Convention (BWC) on several occasions. Moreover, several initiatives are underway to advance biosecurity and safety. However, these initiatives are often context specific and the effective implementation of biosecurity and biosafety measures around the globe remains inadequate. To address this gap, in 2022, France, Senegal and Togo submitted a revised proposal to the BWC for the “establishment of an international platform dedicated to biosecurity and biosafety: SecBio”. The proposal includes three pillars: a searchable repository for biosafety- and biosecurity-related materials; a learning module; and a forum for expert networking to exchange information, data and best practices. To this end, this report draws lessons from past initiatives to develop repositories, learning modules and expert forums in order to inform the development of the SecBio platform (and any such similar initiatives). The report begins with an overview of the importance of biosafety and biosecurity in the context of the BWC. It then proceeds to look at each of the platform pillars in turn, drawing from past experiences to identify lessons and develop options for state parties to consider.
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