For many years, Biology, in general, was a discipline considered to be similar to library sciences, due to the practice of collecting specimens and samples and cataloging them. (I made a herbarium for my high school project.) However, since the 1970s, the advancements in biologia molecolare and in allied areas of biological ricerca, has made Biology diversified. It is no longer a library science. Also, the need for interdisciplinary research has become more prominent. This is evident,specifically in Computational Biology and Bioinformatica, with scientists from diverse background expertise, working on a common problem. In the current scenario, with the advent of newer technologies and techniques, interdisciplinary and integrative scientific research skills are in high demand.
La biologia computazionale e la bioinformatica è una delle aree, dove gli scienziati con diverse competenze di fondo per dare risultati spettacolari. La seguente citazione riassume eloquentemente i benefici della ricerca interdisciplinare e integrativa.
One of the most fascinating issues we’ve encountered is the notably different ways of thinking that typically characterize biologists and computer scientists. Il biologo raccoglie conoscenze, spesso descrive il suo lavoro come se stesse raccontando una storia, si sforza di trarre conclusioni e costruire modelli, e apprezza che le eccezioni sono altrettanto comuni quanto le regole nel nostro mondo biologico. Confrontate questo con l'informatico orientato alla logica e ai processi, per il quale le regole e l'ottimizzazione sono gli obiettivi, e avrete il potenziale per una comunicazione errata. I due gruppi, dato lo stesso problema, faranno domande diverse, coglieranno dettagli diversi, useranno metafore diverse per descrivere il problema, e arriveranno alla situazione con presupposti diversi.
Da dove cominciare?
In Biologia Computazionale, algoritmi non intesi o inventati per risolvere problemi biologici sono stati implementati con successo e gli strumenti sviluppati hanno fatto progredire immensamente il campo [3]. For example, dynamic programming, intended for finding the shortest path, was successfully applied for aligning sequences (both global and local alignment). An extension of the same is BLAST, a popular and essential tool for biologists to identify homologs for a given sequence. Thus, knowledge of algorithms and updating one with variants of the algorithms is essential for a computational biologist.
Con l'avvento di nuove tecnologie e tecniche, le capacità di ricerca scientifica interdisciplinare e integrativa sono molto richieste.
If you are a biologist, having the time tested routine laboratory work, would make you ask the question “I really don’t have time for this!”. And, you are right. But, think it in this way, the field of Computational Biology and Bioinformatics, was developed and nurtured by pioneers were physicists, biologists, chemists, statisticians, etc. Going out of the comfort zone, and listening to researchers from other areas over coffee or a drink is an excellent way to think out of the box. Conferences are a mine field, in this respect. Rather than listening to someone talking about their research (assuming that the research majorly overlaps your focused area, and most likely you have heard their talk on a different occasion), which will eventually be read by me in a few months; one can search for talks that have very less to do with your research. Such opportunities provide brainstorming ideas to implement techniques from other fields to your own research, more specifically Computational Biology and Bioinformatics.
If you don’t like meeting people, then following Twitter, research blogs, and joining discussion forums are the best alternatives.
Non si richiede di diventare esperti in tutto. Piuttosto l'obiettivo è quello di essere a conoscenza di strumenti, risorse e metodi che sono destinati ad un altro scopo, ma uno li modifica per i propri bisogni. Per esempio, gli algoritmi genetici (GA) sono ispirati dagli eventi di ricombinazione che si osservano in biologia. Così, rendendo le tecniche basate su GA più ottimizzate e abbastanza popolari. È anche notevole che i metodi di docking molecolare basati su GA sono ugualmente popolari nella biologia computazionale e nella bioinformatica, in particolare per la progettazione di farmaci.
The potential of using statistiche, matematica, computer science and signal processing in biology is immense. The key to develop an integrative research is communication. Communication with colleagues from other departments is the key. Also, a knack for looking out where the field is moving towards helps. Some interdisciplinary research in computational biology yielding groundbreaking results will be in discussed in subsequent posts.
Il tempo delle scienze integrative è ora!
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